Soils were sampled in three types of wetlands from the young (A) and old (B) reclaimed regions of the Pearl River Estuary. They were analyzed for total concentrations of heavy metals to investigate their distributions and pollution levels in both regions. Results showed that most heavy metals in ditch and riparian wetlands did not significantly differ from those in reclaimed wetlands in A region, while significantly lower for Cd, Cu, Pb, and Zn in reclaimed wetlands in B region, suggesting higher effects of long-term reclamation. Iron, Cr and Cu were identified as metal pollutants of primary concern and had higher contributions to the total toxic units compared to other metals. Almost all metals exceeded their lowest effect levels and Fe and Cr even exceeded the severe effect levels. Multivariate analysis shows that Fe and Mn are controlled by parent rocks and other metals mainly originate from anthropogenic source.

Metal (Cr, Co, Cu, Zn, Cd, Pb, Ni) and metalloid (As) accumulation was studied in roadside soil and wild rat (Rattus sp.) samples from near a Pb–Zn mine (Kabwe, Zambia) and the capital city of Zambia (Lusaka). The concentrations of the seven metals and As in the soil samples and Pb in the rat tissue samples were quantified using atomic absorption spectroscopy. The concentrations of Pb, Zn, Cu, Cd, and As in Kabwe soil were much higher than benchmark values. Geographic Information System analysis indicated the source of metal pollution was mining and smelting activity. Interestingly, the area south of the mine was more highly contaminated even though the prevailing wind flow was westward. Wild rats from Kabwe had much higher tissue concentrations of Pb than those from Lusaka. Their body weight and renal Pb levels were negatively correlated, which suggests that mining activity might affect terrestrial animals in Kabwe.

The environmental risks of antibiotics have attracted lots of research attention, but their environmental behavior is not clear yet. Functionalized carbon nanotubes (CNTs) were used as model adsorbents and sulfamethoxazole (SMX) was used as a model antibiotic to investigate the effect of both cations (Ca²⁺, Cs⁺) and anions (phosphate) on antibiotics adsorption. Various mechanisms (such as electrostatic interaction, hydrophobic interaction, π–π and hydrogen bonds) play roles in SMX adsorption. Cations and anions could “wedge into” these mechanisms and thus alter SMX adsorption. This study emphasized that both increased and decreased SMX adsorption could be observed with the addition of cations/anions, depending on environmental conditions (such as pH in this current study). The net effect is the balance between the increased and decreased effects. The contribution of different mechanisms to the overall antibiotic adsorption on solid particles should be identified to accurately predict the apparent effect by cations and anions.

The Tula Valley receives untreated wastewater from Mexico City for agricultural irrigation, half of which infiltrates to aquifers from where drinking water is extracted. Samples of wastewater and infiltrated water from three areas of the valley were analyzed for microorganisms, organic micropollutants, and some basic parameters. Concentrations of microorganisms in the infiltrated water were generally very low but the incidence of fecal coliforms (present in 68% of samples), somatic bacteriophages (36%), Giardia spp. (14%), and helminth eggs (8%) suggested a health risk. Organic micropollutants, often present at high concentrations in the wastewater, were generally absent from the infiltrated water except carbamazepine which was in 55% of samples (up to 193 ng/L). There was no correlation between carbamazepine concentrations and the presence of microorganisms but highest concentrations of carbamazepine and boron coincided. A treatment such as nanofiltration would be necessary for the infiltrated water to be a safe potable supply.

A dynamic fugacity model was developed to simulate the spatial and seasonal variations of PAHs in Haihe Plain, China. The calculated and measured concentrations exhibited good consistency in magnitude with deviations within a factor of 4 in air and 2 in soil. The spatial distributions of PAHs in air were mainly controlled by emission while the seasonal variations were dominated by emission and gas–particle partition. In soil, the spatial distributions of PAHs were controlled by the soil organic carbon content while the seasonal variations were insignificant. The severest soil contamination was observed in Shanxi and followed by the southwest of Hebei province. Transfer fluxes of total PAHs between air and soil were calculated. The spatial distribution of air-to-soil flux was closely related to the landcover while the soil-to-air flux changed with soil organic matter content. Monte Carlo simulation was done to evaluate the uncertainty of the estimated results in air.

Source-contribution assessment of ambient NO₂ concentration was performed at Pantnagar, India through simulation of two urban mathematical dispersive models namely Gaussian Finite Line Source Model (GFLSM) and Industrial Source Complex Model (ISCST-3) and model performances were evaluated. Principal approaches were development of comprehensive emission inventory, monitoring of traffic density and regional air quality and conclusively simulation of urban dispersive models. Initially, 18 industries were found responsible for emission of 39.11 kg/h of NO₂ through 43 elevated stacks. Further, vehicular emission potential in terms of NO₂ was computed as 7.1 kg/h. Air quality monitoring delineates an annual average NO₂ concentration of 32.6 μg/m³. Finally, GFLSM and ISCST-3 were simulated in conjunction with developed emission inventories and existing meteorological conditions. Models simulation indicated that contribution of NO₂ from industrial and vehicular source was in a range of 45–70% and 9–39%, respectively. Further, statistical analysis revealed satisfactory model performance with an aggregate accuracy of 61.9%.