Exploring the abundance and characteristics of litter in Lithuanian riversides: a citizen science approach

To gain a better understanding of the sources and ecological effects of plastic contamination in Lithuanian rivers, as well as to provide guidance for mitigation, monitoring is necessary. This is a logistically and financially demanding endeavor, particularly in the case of microplastics. Citizen science provides a viable option for sampling sites that are accessible, thus enabling the monitoring of wide areas. In Lithuania, a citizen science approach was employed, with schoolchildren examining litter at riversides and identifying potential sources at 24 sampling sites in Autumn 2022 and 32 in Spring 2023, covering both large and small rivers. The maximum amount of 220 items per location was registered in Autumn 2022, whereas 111 items per location were registered in Spring 2023. The two main types of microlitter discovered were plastic (34-42%) and cigarette butts (17-22%), with glass, paper, and metal also present, which suggests that recreational visitors are the main source of litter. By K-means clustering analysis, all locations were divided into four clusters according to litter composition. To sum up, the findings of this study illustrate the importance of citizen science in providing insight into the contamination of Lithuanian rivers, which can be used to inform the development of conservation strategies.

Multiphase migration and transformation of BTEX on groundwater table fluctuation in riparian petrochemical sites

Light non-aqueous phase liquids (LNAPL) are considered to be a composition-based risk, containing multiple chemical ingredients that release dissolved- and vapor-phase plumes. In dissolved form, there is a saturation-based risk as the water source expands, affecting groundwater aquifers on a larger scale in the aquifer. As a typical pollutant found in petrochemical contaminated sites, the migration and transformation of benzene, toluene, ethylbenzene, and o-xylene (BTEX) between gas, aqueous, and NAPL phases are distinctly affected by groundwater table fluctuation (GTF). BTEX multiphase migration and transformation pattern in a petrochemical factory at the riverside was simulated based on the TMVOC model in differentiating pollution distribution and interphase transformation under stable or fluctuating groundwater tables conditions. TMVOC model performed an excellent simulation effect on the migration and transformation of BTEX in GTF circumstances. In comparison with the stable groundwater table condition, the BTEX pollution depth under GTF increased by 0.5 m, the pollution area increased by 25%, and the total mass increased by 0.12 × 10² kg. In both cases, the mass reduction of NAPL-phase pollutants was more significant than the total mass reduction of pollutants, and GTF further promoted the mass conversion of NAPL-phase pollutants to water pollutants. Prominently, as the groundwater table rises, the GTF can correct for evacuation, and the transport flux of gaseous pollutants at the atmospheric boundary decreases with increasing transport distance. Furthermore, descended groundwater table will intensify the transmission flux of gaseous pollutants at the atmospheric boundary with the transmission range expanding, which can be harmful to human health on the surface due to gaseous pollutants entering into the air.

Dynamic Panel Data Modeling and Surveillance of COVID-19 in Metropolitan Areas in the United States: Longitudinal Trend Analysis

Background

The COVID-19 pandemic has had profound and differential impacts on metropolitan areas across the United States and around the world. Within the United States, metropolitan areas that were hit earliest with the pandemic and reacted with scientifically based health policy were able to contain the virus by late spring. For other areas that kept businesses open, the first wave in the United States hit in mid-summer. As the weather turns colder, universities resume classes, and people tire of lockdowns, a second wave is ascending in both metropolitan and rural areas. It becomes more obvious that additional SARS-CoV-2 surveillance is needed at the local level to track recent shifts in the pandemic, rates of increase, and persistence.

Objective

The goal of this study is to provide advanced surveillance metrics for COVID-19 transmission that account for speed, acceleration, jerk and persistence, and weekly shifts, to better understand and manage risk in metropolitan areas. Existing surveillance measures coupled with our dynamic metrics of transmission will inform health policy to control the COVID-19 pandemic until, and after, an effective vaccine is developed. Here, we provide values for novel indicators to measure COVID-19 transmission at the metropolitan area level.

Methods

Using a longitudinal trend analysis study design, we extracted 260 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in the 25 largest US metropolitan areas as a function of the prior number of cases and weekly shift variables based on a dynamic panel data model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R.

Results

Minneapolis and Chicago have the greatest average number of daily new positive results per standardized 100,000 population (which we refer to as speed). Extreme behavior in Minneapolis showed an increase in speed from 17 to 30 (67%) in 1 week. The jerk and acceleration calculated for these areas also showed extreme behavior. The dynamic panel data model shows that Minneapolis, Chicago, and Detroit have the largest persistence effects, meaning that new cases pertaining to a specific week are statistically attributable to new cases from the prior week.

Conclusions

Three of the metropolitan areas with historically early and harsh winters have the highest persistence effects out of the top 25 most populous metropolitan areas in the United States at the beginning of their cold weather season. With these persistence effects, and with indoor activities becoming more popular as the weather gets colder, stringent COVID-19 regulations will be more important than ever to flatten the second wave of the pandemic. As colder weather grips more of the nation, southern metropolitan areas may also see large spikes in the number of cases.

The interaction of heavy metals and nutrients present in soil and native plants with arbuscular mycorrhizae on the riverside in the Matanza-Riachuelo River Basin (Argentina)

This study assessed the contamination by heavy metals (Cr, Cu, Pb, Zn), and nutrients (N, P) in soils and native plants, and the effect of the concentration of those elements with the density of arbuscular-mycorrhizal (AM) spores in soil and colonization in roots from the riverside of the Matanza-Riachuelo River Basin (MRRB). The concentration of metals and nutrients in soils and plants (Eleocharis montana, Cyperus eragrostis, Hydrocotyle bonariensis) increased from the upper sites (8 km from headwaters) to the lower sites (6 km from the mouth of the Riachuelo River) of the basin. AM-colonization on the roots of H. bonariensis and spore density in soil decreased as the concentrations of metals in soil and plant tissues increased from the upper to lower sites of the basin within a consistent gradient of contamination associated with land use, soil disturbance, population, and chemicals discharged into the streams and rivers along the MRRB. The general trends for all metals in plant tissue were to have highest concentrations in roots, then in rhizomes and lowest in aerial biomass. The translocation (TF) and bioconcentration (BCF) factors decreased in plants which grow from the upper sites to the lower sites of the basin. The plants tolerated a wide range in type and quantity of contamination along the basin by concentrating more metals and nutrients in roots than in aboveground tissue. The AM spore density in soil and colonization in roots of H. bonariensis decreased with the increase of the degree of contamination (Dc) in soil.