Areas Of High Population Density Research Articles

Dynamics of a Memory‐Based Diffusion Model With Maturation Delay and Spatial Heterogeneity

ABSTRACTIn this paper, we consider a single memory‐based diffusion population model with maturation delay, spatial heterogeneity, and Neumann boundary condition. When the integral of the intrinsic growth rate over the domain is nonnegative, we obtain sufficient conditions for the local stability of the positive steady state and the critical values of maturation delay for the associated Hopf bifurcation. When the integral of the intrinsic growth rate over the domain is negative, considering that the characteristic equation involves a non‐self‐adjoint operator and two delays, we utilize a geometric method to determine all bifurcation points in terms of memory and maturation delays. The impact of spatial heterogeneity on the distribution of solutions is also examined via numerical simulations. It is found that the core area of high population density is coincident with the source area of growth rate. This suggests the importance of spatial heterogeneity in shaping the distribution and dynamics of the species.

Evidence of repeated zoonotic pathogen spillover events at ecological boundaries.

Anthropogenic modifications to the landscape have altered several ecological processes worldwide, creating new ecological boundaries at the human/wildlife interface. Outbreaks of zoonotic pathogens often occur at these ecological boundaries, but the mechanisms behind new emergences remain drastically understudied. Here, we test for the influence of two types of ecosystem boundaries on spillover risk: (1) biotic transition zones such as species range edges and transitions between ecoregions and (2) land use transition zones where wild landscapes occur in close proximity to heavily impacted areas of high human population density. Using ebolavirus as a model system and an ensemble machine learning modeling framework, we investigated the role of likely reservoir (bats) and accidental host (primates) range edges and patterns of land use (defined using SEDAC categories) on past spillover events. Our results show that overlapping species range edges and heightened habitat diversity increase ebolavirus outbreaks risk. Moreover, we show that gradual transition zones, represent by high proportion of rangelands, acts as a buffer to reduces outbreak risks. With increasing landscape changes worldwide, we provide novel ecological and evolutionary insights into our understanding of zoonotic pathogen emergence and highlight the risk of aggressively developing ecological boundaries.

Phenolic Ecotoxins in River Water: Survey on Knowledge and Practices of Road-Side Food Vendors Operating Along River Chania Bank Fringes in Thika Sub- County, Kenya

Purpose: Phenolic ecotoxins consumed in raw surface water from river sources has been implicated in causing diseases of high burden such as cancers, in Kenya. This study was conducted in Thika Sub County, and data collected from roadside food vendors and food hawkers who operate small scale street food business along the fringes and banks of River Chania. The study’s objective was to establish the knowledge on Phenolic ecotoxins present in river water and practices of the study respondents. Methodology: A crossectional descriptive study design was used, in which combined interviews and questionnaire enquiries conducted from, n=341, small-scale road side food vendors and hawkers was analyzed. Findings: Data reveals that none of the respondents had knowledge on Phenolic ecotoxin contaminants and additionally a strongly associated correlation (P<0.001, χ222.6 and df 1), further augments the disclosure that, poor knowledge of raw river water safety and hygiene does result to body harm and ill health. Unique Contribution to Theory, Policy and Practice: There is increased need and effort to scale up the sensitization and awareness on exposure to harmful ecotoxin contaminants from the use of raw river water. Water decontamination mobile units should be considered and introduced especially in urban areas of high population density, transversed by rivers.

Patterns of animal rabies in the Nizhny Novgorod region of Russia (2012-2022): the analysis of risk factors.

Animal rabies is a viral disease that poses a significant threat to domestic and wild animal populations, with devastating consequences for animal health and human life. Understanding and assessing the risk factors associated with the transmission and persistence of the rabies virus in wild and domestic animal populations is crucial for developing effective strategies to control and mitigate cases. Studies of the spatial and temporal distribution of rabies cases in the Nizhny Novgorod region during 2012-2022 provided epidemiological evidence of the circulation of infection between animals in the presence of vaccination. Among the wild animals in the area, red foxes play a major role in the spread of rabies, accounting for 96.4% of all wild animal cases. We used spatiotemporal cluster analysis and a negative binomial regression algorithm to study the relationships between animal rabies burden by municipality and a series of environmental and sociodemographic factors. The spatiotemporal cluster analysis suggests the concentration of wild animal rabies cases in the areas of high fox population density and insufficient vaccination rates. The regression models showed satisfactory performance in explaining the observed distribution of rabies in different animals (R 2 = 0.71, 0.76, and 0.79 in the models for wild, domestic and all animals respectively), with rabies vaccination coverage and fox population density being among the main risk factors. We believe that this study can provide valuable information for a better understanding of the geographical and temporal patterns of rabies distribution in different animal species, and will provide a basis for the development of density-dependent planning of vaccination campaigns.

Pinpointing sources of pollution using citizen science and hyperlocal low-cost mobile source apportionment

Currently, methodologies for the identification and apportionment of air pollution sources are not widely applied due to their high cost. We present a new approach, combining mobile measurements from multiple sensors collected from the daily walks of citizen scientists, in a high population density area of Birmingham, UK. The methodology successfully pinpoints the different sources affecting the local air quality in the area using only a handful of measurements. It was found that regional sources of pollution were mostly responsible for the PM2.5 and PM1 concentrations. In contrast, PM10 was mostly associated with local sources. The total particle number and the lung deposited surface area of PM were almost solely associated with traffic, while black carbon was associated with both the sources from the urban background and local traffic. Our analysis showed that while the effect of the hyperlocal sources, such as emissions from construction works or traffic, do not exceed the distance of a couple of hundred meters, they can influence the health of thousands of people in densely populated areas. Thus, using this novel approach we illustrate the limitations of the present measurement network paradigm and offer an alternative and versatile approach to understanding the hyperlocal factors that affect urban air quality. Mobile monitoring by citizen scientists is shown to have huge potential to enhance spatiotemporal resolution of air quality data without the need of extensive and expensive campaigns.

Spatial and seasonal variations of atmospheric microplastics in high and low population density areas at the intersection of tropical and subtropical regions

There is limited information regarding spatial and seasonal variations of atmospheric microplastics (MPs) and factors influencing MPs at the intersection of tropical and subtropical regions. A one-year study was conducted at sites in a high-population-density village (HPDV) and a low-population-density village (LPDV) in Taiwan to investigate the characteristics and influencing factors of airborne MPs. The predominant shapes, sizes, and polymer compositions of MPs were fragments, 3 to 25 and 26–50 μm, and polyamide at both sites. Seasonal variation in MP morphologies was not significant. Average MP concentrations were 2.20 ± 2.97 particles/m3 and 1.92 ± 2.35 particles/m3 at the HPDV and LPDV sites, respectively, and did not differ significantly. Higher concentrations and smaller sizes of MPs were found during the summer at both sites, while the predominant wind direction was southerly or southwesterly. In samples with temperatures exceeding 25 °C, the temperature was positively associated with MP concentrations at both the HPDV and LPDV sites. These results reflect that temperature influences the variations in the concentrations and sizes of MPs at our study site. Future research should consider the adverse risks of MP inhalation during the hot season. Moreover, when sites with different population densities and levels of human activity are closed, MP concentrations will not differ significantly between these areas since airflow can transport these particles from high-population-density areas into low-population-density areas in a short time.

Predictability and prediction skill of summertime East/Japan Sea surface temperature events

The East/Japan Sea (EJS), a marginal sea of the Northwestern Pacific, is one of the ocean regions showing the most rapid warming and greatest increases in ocean heatwaves over the last several decades. Predictability and skillful prediction of the summer season EJS variability are crucial, given the increasing severity of ocean temperature events impacting fisheries and reinforcing climate conditions like the East Asian rainy season, which in turn affects adjacent high-population density areas over East Asia. We use observations and the Geophysical Fluid Dynamics Laboratory (GFDL) Seamless System for Prediction and Earth System Research (SPEAR) seasonal forecast system to investigate the summertime EJS Sea Surface Temperature (SST) predictability and prediction skill. The observations and seasonal prediction system show that the summer season EJS SST can be closely linked to the previous winter air-sea coupling and predictable 8–9 months in advance. The SPEAR seasonal prediction system demonstrates skillful forecast of EJS SST events from summer to late fall, with added skill for long-lead forecasts initialized in winter. We find that winter large-scale atmospheric circulations linked to Barents Sea variability can induce persistent surface wind anomalies and corresponding northward Ekman heat transport over the East China Sea. The ocean advection anomalies that enter the EJS in prior seasons appear to play a role in developing anomalous SST during summer, along with instantaneous atmospheric forcing, as the source of long-lead predictability. Our findings provide potential applications of large-scale ocean-atmosphere interactions in understanding and predicting seasonal variability of East Asian marginal seas.

Usability of Community Seismic Network recordings for ground-motion modeling

A source of ground-motion recordings in urban Los Angeles that has seen limited prior application is the Community Seismic Network (CSN), which uses low-cost, micro–electro–mechanical system (MEMS) sensors that are deployed at much higher densities than stations for other networks. We processed CSN data for the 29 earthquakes with M > 4 between July 2012 and January 2023 that produced CSN recordings, including selection of high- and low-pass corner frequencies ( fcHP and fcLP, respectively). Each record was classified as follows: (1) Broadband Record (BBR)—relatively broad usable frequency range from fcHP < 0.5 to fcLP > 10 Hz; (2) Narrowband Record (NBR)—limited usable frequency range relative to those for BBR; and (3) Rejected Record (REJ)—noise-dominated. We compare recordings from proximate (within 3 km) CSN and non-CSN stations (screened to only include cases of similar surface geology and favorable CSN instrument housing). We find similar high- to medium-frequency ground motions (i.e. peak ground acceleration (PGA) and Sa for T < 5 s) from CSN BBR and non-CSN stations, whereas NBRs have lower amplitudes. We examine PGA distributions for BBR and REJ records and find them to be distinguished, on average across the network, at 0.005 g, whereas 0.0015 g was found to be the threshold between usable records (BBR and NBR) and pre-event noise. Recordings with amplitudes near or below these thresholds are generally noise-dominated, reflecting environmental and anthropogenic ground vibrations and instrument noise. We find nominally higher noise levels in areas of high-population density and lower noise levels by a factor of about 1.5 in low-population density areas. By applying the 0.0015 g threshold, limiting distances for the network-average site condition, based on the expected fifth-percentile ground-motion levels, are 89, 210, 280, and 370 km for M 5, 6, 7, and 8 events, respectively.

Evaluation of the Spatial Pattern of Fitness and Leisure Venues at the City Scale

Reasonable layout of fitness and leisure places is an important part of the implementation of the national fitness strategy. The analysis of the spatial pattern and influence mechanism of fitness and leisure places from the perspective of city has certain guiding significance for optimizing urban planning and construction and rationally allocating sports resources. This paper uses kernel density, buffer zone, inverse distance interpolation, Kriging interpolation, geographical detector and other geographical spatial analysis methods to analyze the spatial distribution pattern and distribution causes of five types of fitness and leisure places in counties (cities, districts) under the jurisdiction of Jinhua City. It is found that the overall spatial distribution characteristics of fitness and leisure places in Jinhua City are ' core-periphery ', and different forms of fitness and leisure places show different distribution characteristics. The spatial pattern of fitness and leisure places in Jinhua City has the characteristics of relying on traffic arteries and high-density population areas, and has a positive correlation with the spatial layout of housing prices. Jinhua fitness and leisure places generally have good traffic accessibility.

A study of prehospital EMS response time and influencing factors in the main urban area of Chongqing, China.

Shortening the prehospital emergency medical service (EMS) response time is crucial for saving lives and lowering mortality and disability rates in patients with sudden illnesses. Descriptive analyses of prehospital EMS response time and each component were conducted separately using ambulance trip data from the 120 Dispatch Command Centre in the main urban area of Chongqing in 2021, and then, logistic regression analyses were used to explore the influencing factors. The median prehospital EMS response time in the main urban area of Chongqing was 14.52 min and the mean was 16.14 min. A 44.89% of prehospital EMS response time exceeded 15 min. Response time was more likely to surpass this threshold during peak hours and in high population density areas. Conversely, lower probabilities exceeding 15 min were observed during the night shift, summer, and autumn seasons, and areas with a high density of emergency station. 33.28% of preparation time was >3 min, with the night shift and high population density areas more likely to be >3 min, while for the summer and autumn seasons, high Gross National Product (GDP) per capita areas had a lower likelihood of having preparation time >3 min. 45.52% of travel time was >11 min, with peak hours, summer and autumn, and high GDP per capita areas more likely to have had a travel time >11 min, while night shift and high emergency station density areas had a lower likelihood of travel time >11 min. The primary factors influencing prehospital EMS response time were shifts, traffic scenarios, seasons, GDP per capita, emergency station density, and population density. Relevant departments can devise effective interventions to reduce response time through resource allocation and department coordination, staff training and work arrangement optimisation, as well as public participation and education, thereby enhancing the efficiency of prehospital emergency medical services.

Community use of school grounds outside of school hours

ABSTRACT Physical activity in childhood is essential for healthy development and wellbeing and school grounds can provide neighbourhood access to safe play spaces. This study examines the relationship between school demographics (school size, school decile, ethnicity of students and population density) and whether school grounds are open or closed for community use outside school hours. Data were gathered from 391 primary and intermediate schools across Tāmaki Makaurau (Auckland), Aotearoa New Zealand (84% of Auckland schools) with 250 schools participating in the full survey. The results indicate that higher school decile and lower population density are associated with school grounds being available for community use. This result is concerning. With closed school grounds more likely to be in lower socio-economic and higher population density areas, the children most affected are the same group who have fewer opportunities and less spaces for active play. The main reason schools closed their grounds was ‘vandalism /graffiti/theft concerns’. Low decile schools whose grounds were open outside of school hours shared a similar commitment to involve their communities widely in school activities and found doing so decreased the levels of vandalism. Their approach may offer useful insights to schools that are currently closed.

An empirical analysis of the coupling and coordinated development of new urbanization and ecological welfare performance in China’s Chengdu–Chongqing economic circle

New urbanization (NU) and ecological welfare performance (EWP) play pivotal roles in achieving sustainable urban development, with both emphasizing social equity and environmental management. Exploring the coordinated relationship between EWP and NU is invaluable for understanding the symbiotic interplay between humans and nature. We constructed a framework to elucidate the coupling mechanism of EWP and NU from the perspective of systems theory. We quantified the levels of NU and EWP utilizing the entropy weighting method and the super-efficient SBM method, respectively. Furthermore, we assessed the degree of coupling coordination between the two using the coupling coordination degree model (CCDM). Spatial and temporal evolution analysis was conducted, and factors influencing the degree of coupling coordination between EWP and NU were explored through a spatial–temporal geographically-weighted regression model (GTWR). The results indicate: (1) During the study period, the average annual increase in EWP in the study area was 2.59%, with a narrowing relative gap between cities. Conversely, the average annual increase in the level of NU was 7.6%, with demographic and economic dimensions carrying the highest weights. (2) The type of coupling coordination between EWP and NU transitions from basic coordination to moderate coordination, with the development of EWP lagging behind that of NU. (3) City size demonstrates a positive yet diminishing trend on the coupling coordination level, with economic development exerting the greatest influence and exhibiting a "V" trend, while the impact of green technology innovation diminishes negatively. Additionally, regional disparities are significant, with city size exhibiting a negative impact in areas of high population density and low economic levels, and green technology innovation showing notable polarization characteristics in core cities. These findings serve as a foundation for fostering coordinated ecological development amid the rapid urbanization process of the Chengdu–Chongqing Economic Circle.

Assessment of Solid Waste Management Practices Following Private Partnership Operations in Zaria Urban Area of Kaduna, Nigeria

The safe disposal of municipal waste is very important in promoting a healthy environment. High-quality public services and promoting competition in the waste management sector leads to the formation of private sector participation (PSP) to handle solid waste management in Kaduna. A multi-stage sampling technique was adopted which involves dividing the local government into localities. Stage two involves the purposive sampling technique which was adopted in selecting locality with high population and low population density areas, a total of 400 households from both strata were interviewed. Descriptive statistics was used to analyse the information from the questionnaires and results were presented using frequency tables and charts. The findings revealed that quality of service among the PSP operators recorded high success in the high-income areas and much less in the low and medium-income areas. On average, industry productivity was 5.63 tonnes per day per vehicle. 12 out of which in the study area were above this average and in meeting increased productivity, year of experience in operations, number of trips made, number of times trucks were serviced, and adhering to regulatory agency requirements were among the factors influencing company’s productivity in the state. It also shows less effectiveness of the system in waste management in the area. The study, therefore, recommends that regulatory agency should be more aggressive in playing their statutory roles of managing the PSP operators.

Geospatial Distribution of Prenatally and Postnatally Diagnosed Congenital Heart Disease: Implications for Equitable Care from a Fetal Heart Society Research Collaborative Study

To characterize patterns in the geospatial distribution of pre- and postnatally diagnosed congenital heart disease (CHD) across 6 surgical centers. A retrospective, multicenter case series from the Fetal Heart Society identified patients at 6 centers from 2012 through 2016 with prenatally (PrND) or postnatally (PoND) diagnosed hypoplastic left heart syndrome (HLHS) or d-transposition of the great arteries (TGA). Geospatial analysis for clustering was done by the average nearest neighbor (ANN) tool or optimized hot spot tool, depending on spatial unit and data type. Both point location and county case rate per 10 000 live births were assessed for geographic clustering or dispersion. Of the 453 CHD cases, 26% were PoND (n=117), and 74% were PrND (n=336). PrND cases, in all but one center, displayed significant geographic clustering by the ANN. Conversely, PoND cases tended toward geographic dispersion. Dispersion of PoND HLHS occurred in 2 centers (ANN=1.59, P<.001; and 1.47, P=.016), and PoND TGA occurred in 2 centers (ANN=1.22, P<.05; and ANN=1.73, P<.001). Hot spot analysis of all CHD cases (TGA and HLHS combined) revealed clustering near areas of high population density and the tertiary surgical center. Hot spot analysis of county-level case rate, accounting for population density, found variable clustering patterns. Geographic dispersion among postnatally detected CHD highlights the need for a wider reach of prenatal cardiac diagnosis tailored to the specific needs of a community. Geospatial analysis can support centers in improving the equitable delivery of prenatal care.

Earthquake Detection and Alerting system using ANN and IOT

Earthquakes are one of the deadliest natural disasters. The damage caused by earthquakes is very destructive and the number of deaths are at a very large scale. The National Earthquake Information Centre now detects about 20,000 earthquakes around the globe each year, or approximately 55 per day. Many of the Earth’s earthquake zones coincide with areas of high population density. When a large earthquake occurs in such areas, the results can be catastrophic. The basic parameter to determine an earthquake before it was going to occur is the p wave or primary shock wave which is not destructive to infrastructure because it travels parallel to the propagation of seismic wave. A series of destructive waves that follows p waves are s waves or secondary waves which has a speed of about 60% that of p waves. The movement of the s wave is perpendicular to the direction of propagation of the seismic wave and hence it is extremely risky to infrastructures and cause a lot of damage. This research aims to build an earthquake detection and alerting system using a low-cost accelerometer, ESP32 Wi-Fi module, and ANN algorithm. The input earthquake data is taken by the accelerometer and with the help of the ESP32 Wi-Fi module the data is sent to a system that processes the ANN algorithm with Multi layered perceptron trained with stochastic gradient descent learning algorithm and detects whether an earthquake is going to occur or not and alerts users with ESP32 Wi-Fi module. Key Words: Artificial Neural Networks, ESP32, Accelerometer, Earthquake, Multi-layer perceptron, Sigmoid function, Stochastic Gradient Descent.

Adaptive Time-Location Sampling for COMPASS: A SARS-CoV-2 Prevalence Study in Fifteen Diverse Communities in the United States.

COVID-19 has placed a disproportionate burden on underserved racial and ethnic groups, community members working in essential industries, those living in areas of high population density, and those reliant on in-person services such as transportation. The goal of this study was to estimate the cross-sectional prevalence of SARS-CoV-2 (active SARS-CoV-2 or prior SARS-CoV-2 infection) in children and adults attending public venues in 15 sociodemographically diverse communities in the United States and to develop a statistical design that could be rigorously implemented amidst unpredictable stay-at-home COVID-19 guidelines. We used time-location sampling with complex sampling involving stratification, clustering of units, and unequal probabilities of selection to recruit individuals from selected communities. We safely conducted informed consent, specimen collection, and face-to-face interviews outside of public venues immediately following recruitment. We developed an innovative sampling design that adapted to constraints such as closure of venues, changing infection hotspots, and uncertain policies. We updated both the sampling frame and the selection probabilities over time using information acquired from prior weeks. We created site-specific survey weights that adjusted sampling probabilities for nonresponse and calibrated to county-level margins on age and sex at birth. Although the study itself was specific to COVID-19, the strategies presented in this article could serve as a case study that can be adapted for performing population-level inferences in similar settings and could help inform rapid and effective responses to future global public health challenges.

Planning location of parcel lockers using group Analytic Hierarchy Process in Spherical Fuzzy environment

Parcel lockers have emerged as an effective solution to address inefficiencies in last-mile delivery. However, the selection of an appropriate location plays a crucial role in ensuring optimal service and enhanced logistic performance. To address this challenge, this work aims to define the best location for parcel lockers in the capital of Ireland, Dublin by conducting a novel decision-making model. The Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) has been adopted to deal with the uncertainty in the decision maker preferences, while the Euclidean Distance-Based Aggregation Method (EDBAM) has been conducted to aggregate the decision makers preferences. The proposed integrated model is an applicable approach to elude AHP deterministic disadvantages, moreover, it is the first application of SF-AHP and EDBAM to select parcel lockers’ location. The findings, including the identification of the top three optimal locations, namely “Post office,” “On commercial area,” and “High population density area,” along with their respective weight scores, provide valuable insights for policymakers making strategic decisions regarding parcel locker placements in Dublin city.

The spatial dynamics of Ukraine air quality impacted by the war and pandemic

ABSTRACT In recent years, our world has experienced significant disruptions due to the COVID-19 pandemic, and Russia's 2022 invasion of Ukraine, impacting human activities and the global environment. This paper explored air quality changes in Ukraine due to COVID-19, and Russia's invasion of Ukraine using on-demand with a what-you-see-is-what-you-get approach. During the COVID-19 pandemic, strict quarantine policies in Ukraine led to a 2% reduction in tropospheric NO2 concentration before the lockdown and 4% during the lockdown period. Cities like Kyiv, Donetsk, and Dnipro exhibited reductions of 5%, 11%, and 16%, respectively. Total SO2 column concentration decreased by 6% before the lockdown and 2.5% during the lockdown period, except in high population density areas. Kyiv showed the highest reduction of 17% in SO2 concentration, while Donetsk and Dnipro exhibited an 11% reduction. However, during the Russian invasion, there was a significant increase in tropospheric NO2 concentration in heavily destroyed Kharkiv while most eastern regions experienced a reduction. The total SO2 column was 48% higher before the war but reduced throughout the country after the war, except for in Kyiv and a few central regions. These findings can contribute to analyzing air pollution and building digital twin simulations for future reconstruction scenarios.

The effect of population density on outcomes of major trauma patients in Ireland

BackgroundTime-sensitive emergencies in areas of low population density have statistically poorer outcomes. This includes incidents of major trauma. This study assesses the effect that population density at a receiving hospital of a major trauma patient has on survival. MethodsPatients meeting Trauma Audit Research Network criteria for major trauma from 2016 to 2020 in Ireland were included in this retrospective observational study. Incident data were retrieved from the Major Trauma Audit, while data on population density were calculated from Irish state sources. The primary outcome measure of survival to discharge was compared to population density using logistic regression, adjusted for demographic and incident variables. Records were divided into population density tertiles to assess for between-group differences in potential predictor variables. ResultsPopulation density at a receiving hospital had no impact on mortality in Irish major trauma patients from our logistic regression model (OR = 1.01, 95% CI 0.98–1.05, p = 0.53). Factors that did have an impact were age, Charlson Comorbidity Index, Injury Severity Score, and the presence of an Orthopaedic Surgery service at the receiving hospital (all p < 0.001). Age and Charlson Comorbidity Index differed slightly by population density tertile; both were higher in areas of high population density (all p < 0.001). ConclusionsSurvival to discharge in Irish major trauma patients does not differ substantially based on population density. This is an important finding as Ireland moves to a new trauma system, with features based on population distribution. An Orthopaedic Surgery service is an important feature of a major trauma receiving hospital and its presence improves outcomes.

The distribution and characterisation of microplastics in air, surface water and sediment within a major river system

Rivers are key pathways for the transfer of microplastics (MP) to marine environments. However, there are considerable uncertainties about the amount of microplastics transported by rivers to the ocean; this results in inaccuracies in our understanding of microplastic quantity and transport by freshwater systems. Additionally, it has been suggested that rivers may represent long-term sinks, with microplastics accumulating in sediment due to their high density or other biological, chemical, and physical factors. The atmosphere is also an important pathway by which airborne microplastics may enter aquatic habitats. Here, we compare for first time microplastics type and concentration in these key environmental mediums (air, water and sediment) along a major river (Ganges), from sea to source to understand 1) the abundance, 2) the spatial distribution, and 3) characteristics. Mean microplastic abundance settling from the atmosphere was 41.12 MP m2 day−1; while concentrations in sediment were 57.00 MP kg−1 and in water were 0.05 MP L−1. Across all sites and environmental mediums, rayon (synthetically altered cellulose) was the dominant polymer (54–82 %), followed by acrylic (6–23 %) and polyester (9–17 %). Fibres were the dominant shape (95–99 %) and blue was the most common colour (48–79 %). Across water and sediment environmental mediums, the number of microplastics per sample increased from the source of the Ganges to the sea. Additionally, higher population densities correlated with increased microplastic abundance for air and water samples. We suggest that clothing is likely to be the prominent source of microplastics to the river system, influenced by atmospheric deposition, wastewater and direct input (e.g. handwashing of clothes in the Ganges), especially in high density population areas. However, we suggest that subsequent microplastic release to the marine environment is strongly influenced by polymer type and shape, with a large proportion of denser microplastics settling in sediment prior to the river discharging to the ocean.