Air pollution in the form of fine particulate matter (PM₂.₅) has been linked to adverse respiratory outcomes in children. However, the magnitude of this association in South Asia and sources of PM₂.₅ that drive adverse health effects are largely unknown. This study evaluates associations between short-term variation in ambient PM₂.₅ and incidence of pneumonia and upper respiratory infections among children in Dhaka, Bangladesh. We also perform an exploratory analysis of the PM₂.₅ source composition that is most strongly associated with health endpoints. We leveraged data from health surveillance of children less than five years of age between 2005 and 2014 in Kamalapur, Bangladesh, including daily physician-confirmed diagnoses of pneumonia and upper respiratory infection. Twice-weekly source-apportioned ambient PM₂.₅ measurements were obtained for the same period, and Poisson regression adjusted for time-varying covariates was used to estimate lagged associations between ambient PM₂.₅ and respiratory infection. We use complementary matching and stratification approaches to evaluate whether these associations vary across PM₂.₅ source composition. Total PM₂.₅ mass was associated with a modest increase in incidence of pneumonia, with a peak effect size two days after exposure (rate ratio = 1.032; 95% confidence interval = 1.008–1.056). We did not identify a significant association between PM₂.₅ and upper respiratory infection. Stratified and matching analyses suggested this association was stronger among days when ambient PM₂.₅ had a higher mass percent associated with brick kiln and fugitive lead emissions.: This study suggests that elevated ambient PM₂.₅ contributes to increased incidence of child pneumonia in urban Dhaka, and that this relationship varies among days with different source composition of PM₂.₅.

Previous nationwide studies have reported links between long-term concentrations of fine particulate matter (PM2.5) and COVID-19 infection and mortality rates. In order to translate these results to the state level, we use Bayesian hierarchical models to explore potential links between long-term PM2.5 concentrations and census tract-level rates of COVID-19 outcomes (infections, hospitalizations, and deaths) in Colorado. We explicitly consider how the uncertainty in PM2.5 estimates affects our results by comparing four different PM2.5 surfaces from academic and governmental organizations. After controlling for 20 census tract-level covariates, we find that our results depend heavily on the choice of PM2.5 surface. Using PM2.5 estimates from the United States EPA, we find that a 1 μg/m³ increase in long-term PM2.5 concentrations is associated with a statistically significant 26% increase in the relative risk of hospitalizations and a 34% increase in mortality. Results for all other surfaces and outcomes were not statistically significant. At the same time, we find a clear association between communities of color and COVID-19 outcomes at the Colorado census tract level that is minimally affected by the choice of PM2.5 surface. A per-interquartile range (IQR) increase in the percent of non-African American people of color was associated with a 31%, 43%, and 56% increase in the relative risk of infection, hospitalization, and mortality respectively, while a per-IQR increase in the proportion of non-Hispanic African Americans was associated with a 4% and 7% increase in the relative risk of infections and hospitalizations. The current disagreement among the different PM2.5 estimates is a key factor limiting our ability to link environmental exposures and health outcomes at the census tract level. These results have strong implications for the implementation of an equitable public health response during the crisis and suggest targeted areas for additional air monitoring in Colorado.

Natural colloids such as clays and natural organic matter (NOM) are universally present in environments, which could interact with microplastics (MPs) and thus alter the fate and transport of MPs in porous media. The co-effects of clays and NOM on MPs transport in saturated porous media were systematically explored at both low and high ionic strength (IS) conditions. Specifically, bentonite and humic acid (HA) were employed as representative clays and NOM. 5 mM NaCl and 1 mM CaCl₂ solutions were used as low IS conditions, while 25 mM NaCl and 5 mM CaCl₂ solutions were employed as high IS conditions. We found that formation of MPs-bentonite heteroaggregates had great effects on MPs transport under different conditions. Without HA, the small MPs-bentonite heteroaggregates formed under low IS increased MPs transport via serving as mobile carriers, while larger MPs-bentonite heteroaggregates formed at high IS led to the decreased MPs mobility. When both HA and bentonite were copresent in MPs suspension, we found that HA could inhibit the formation of larger sized MPs-bentonite heteroaggregates. Particularly, when the two types of natural colloids copresent in MPs suspensions, MPs transport behaviors were similar to those with only bentonite present in MPs suspensions at low IS, while MPs transport was greatly increased at high IS comparing with those only with bentonite in suspensions. Clearly, without HA in suspensions, bentonite played the dominant role on MPs transport under all examined conditions concerned in this study. Instead, when both HA and bentonite copresent in MPs suspensions, MPs transport was mainly controlled by bentonite at low IS, while both bentonite and HA had major contributions at high IS. The results showed that under solution conditions concerned in present study, MPs mobility in porous media would be greatly affected (either enhanced or inhibited) by the two types of natural colloids.

The source for Lead (Pb) pollution in soils from the heavily industrialized area located along the coast of the Eastern Mediterranean, Haifa Bay, Northern Israel, is studied using the lead isotopic composition. The uniqueness of the studied data set is that it includes samples of soils, road-wash, and storm-dust sampled for nearly three decades (1988–2017). Road-wash sediments are similar in both elemental and Pb isotopic composition to soils sampled in the same year (2010), indicating re-suspension of local soil, as its origin. Soils sampled during and before 1993 show no evidence for Pb contamination (bulk soil values), although Pb as an additive was already in use. Furthermore, soil overturns hinder the possibility to trace changes in the Pb isotopic composition with time in soils of the same location. Soils sampled from 1995–8 to 2013 were significantly dominated by Post-1992 Pb additive, pointing to Pb’s peak as an additive. Soils Pb and Zn Enrichment factors for most samples are below 5, and their anthropogenic source is likely common. Forest fire enriched Pb and Zn in the soil, and their Pb isotope compositions reflect this enrichment. Lead from the Hod Assaf recycling plant detected up to some 2.5 km away, and although not analyzed in the current study, dioxin-like compounds possibly accompanied Pb.

Coastal sediments, where microplastics (MPs) accumulate, support benthic microalgae (BMA) that contribute to ecosystem functions such as primary production, nutrient recycling and sediment biostabilization. The potential interactions between MPs, BMA and associated properties and functions remain poorly understood. To examine these interactions, a survey of 22 intertidal sites was conducted. MP abundance, size and a suite of MP diversity indices (based on color and shape) were determined from surface sediments alongside biochemical and physical properties. MPs were detected at all sites and dominated by polypropylene (34%), polyester (18%) and polyethylene (11%). Fragment and fiber dominance (16–92% and 6–81% respectively) and color-shape category diversity varied significantly by site. Distance-based linear models demonstrated that estuary-wide, mean grain size and mud were the best predictors of MP abundance-diversity matrices, but variance explained was low (9%). Relationships were improved when the data was split into sandy and muddy habitats. In sandy habitats (<8% mud), physical properties of the bed (mean grain size, mud content and distance from the estuary mouth) were still selected as predictors of MP abundance-diversity (14% variance explained); but a number of bivariate relationships were detected with biochemical properties such as BMA associated pigments and organic matter. In muddy habitats (>8% mud), porewater ammonium was lower when fiber abundance and overall MP diversity were higher. The inclusion of porewater ammonium, organic matter content and pheophytins alongside physical properties explained a greater percentage of the variance in MP abundance-diversity for muddy habitats (21%). The results highlight the importance of examining plastic shapes and MP categories in addition to abundance and emphasize that functionally different habitats should be examined separately to increase our understanding of MP-biota-function relationships.

Organic and inorganic pollutants are often co-sedimentary in soils and have the same sources in the urban environment. The identification of the sources and distribution of combined pollutants is a basic step in risk management. In this study, the levels of polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) were measured in urban park soils in Beijing. Bivariate local Moran’s I and positive matrix factorization (PMF) source apportionment were used to identify the spatial clustering patterns and potential sources of PAHs and HMs, as well as to ultimately define a pollution risk control area. The results revealed an obvious clustered distribution of PAHs and HMs in the park soils. High-high areas were defined as sites containing a complex mixture of pollutants, which were mainly located in the center and north of Beijing. High-low and low-high areas were located outside the city center but had the potential for combined pollution, and therefore require continuous attention. Bivariate local indicators of spatial association (LISA) enabled a more accurate analyses of the mechanism controlling the spatial distribution of PAH and HM combinations in urban parks. The source apportionment indicated that industrial and traffic emissions were the most important sources of the pollutant combinations in urban parks, with traffic emissions accounting for most of the pollution.

Here, we examined the combinational effect of ocean acidification (OA) and mercury (Hg) in the planktonic copepod Pseudodiaptomus annandalei in cross-factored response to different pCO₂ (400, 800 μatm) and Hg (control, 1.0 and 2.5 μg/L) exposures for three generations (F0–F2), followed by single-generation recovery (F3) under clean condition. Several phenotypic traits and Hg accumulation were analyzed for F0–F3. Furthermore, shotgun-based quantitative proteomics was performed for F0 and F2. Our results showed that OA insignificantly influenced the traits. During F0–F2, combined exposure reduced Hg accumulation as compared with the counterpart Hg treatment, supporting the mitigating effect of OA on Hg toxicity in copepods. Proteomics analysis indicated that the copepods probably increased energy production/storage and stress response to ensure physiological resilience against OA. However, Hg induced many toxic events (e.g., energy depletion and degenerated organomorphogenesis/embryogenesis for F0; cell cycle arrest and detrimental stress-defense for F2), which were translated to the population-level adverse outcome, i.e., compromised growth/reproduction. Particularly, compensatory proteome response was identified (e.g., increased immune defense for F0; energetic compensation and enhanced embryogenesis for F2), accounting for a negative interaction between OA and Hg. Together, this study provides the molecular mechanisms behind the effects of OA and Hg pollution in marine copepods.

Harmful algal blooms are increasingly recognized as a threat to the integrity of freshwater reservoirs, which serve as water supplies, wildlife habitats, and recreational attractions. While algal growth and accumulation is controlled by many environmental factors, the relative importance of these factors is unclear, particularly for turbid eutrophic systems. Here we develop and compare two models that test the relative importance of vertical mixing, light, and nutrients for explaining chlorophyll-a variability in shallow (2–3 m) embayments of a eutrophic reservoir, Jordan Lake, North Carolina. One is a multiple linear regression (statistical) model and the other is a process-based (mechanistic) model. Both models are calibrated using a 15-year data record of chlorophyll-a concentration (2003–2018) for the seasonal period of cyanobacteria dominance (June–October). The mechanistic model includes a novel representation of vertical mixing and is calibrated in a Bayesian framework, which allows for data-driven inference of important process rates. Both models show that chlorophyll-a concentration is much more responsive to nutrient variability than mixing, light, or temperature. While both models explain approximately 60% of the variability in chlorophyll-a, the mechanistic model is more robust in cross-validation and provides a more comprehensive assessment of algal drivers. Overall, these models indicate that nutrient reductions, rather than changes in mixing or background turbidity, are critical to controlling cyanobacteria in a shallow eutrophic freshwater system.

The objective of this paper was to incorporate source-meteorological interaction information from two commonly employed atmospheric dispersion models into the land use regression technique for predicting ambient nitrogen dioxide (NO₂), sulphur dioxide (SO₂), and particulate matter (PM₁₀). The study was undertaken across two regions in Durban, South Africa, one with a high industrial profile and a nearby harbour, and the other with a primarily commercial and residential profile. Multiple hybrid models were developed by integrating air pollution dispersion modelling predictions for source specific NO₂, SO₂, and PM₁₀ concentrations into LUR models following the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology to characterise exposure, in Durban. Industrial point sources, ship emissions, domestic fuel burning, and vehicle emissions were key emission sources. Standard linear regression was used to develop annual, summer and winter hybrid models to predict air pollutant concentrations. Higher levels of NO₂ and SO₂ were predicted in south Durban as compared to north Durban as these are industrial related pollutants. Slightly higher levels of PM₁₀ were predicted in north Durban as compared to south Durban and can be attributed to either traffic, bush burning or domestic fuel burning. The hybrid NO₂ models for annual, summer and winter explained 60%, 58% and 63%, respectively, of the variance with traffic, population and harbour being identified as important predictors. The SO₂ models were less robust with lower R² annual (44%), summer (53%) and winter (46%), in which industrial and traffic variables emerged as important predictors. The R² for PM₁₀ models ranged from 80% to 85% with population and urban land use type emerging as predictor variables.

Identifying effective and low-cost agents for the remediation of Pb-contaminated soil is of great importance for field-scale applications. In this study, the feasibility of reusing incinerated sewage sludge ash (ISSA), a waste rich in phosphorus, under activation by oxalic acid (OA) for the remediation of high-Pb contaminated soil was investigated. ISSA and OA were mixed at different proportions for the treatment of the high-Pb contaminated soil (5000 mg/kg). The Pb immobilization efficacy was further examined by both the standard deionized water leaching test and the toxicity characteristic leaching procedure (TCLP). The overall results showed that the use of the ISSA alone and an appropriate mixture of the ISSA and OA could effectively reduce the leachability of Pb from soil. 20% ISSA together with 30% OA (0.2 mol/L) reduced leached Pb concentration by 99%. The main stabilization mechanisms were then explored by different microstructural and spectroscopic analytical techniques including SEM, XRD and FTIR. Apparently, OA released phosphate from the ISSA and Pb from soil via acid attack, which combined and precipitated as stable lead phosphate minerals. However, excessive OA could cause high leaching of phosphate and zinc from the ISSA. Overall, this study indicates that ISSA could be used together with OA to remediate high-Pb contaminated soil, but careful design of mix proportions is necessary before practical application to avoid excessive leaching of phosphate and zinc from the ISSA.