Application of empirical models to adsorption of contaminants on natural heterogeneous sorbents is often challenging due to the uncertainty associated with fitting experimental data and determining adjustable parameters. Sediment samples from contaminated and uncontaminated portions of a study site in Maine, USA were collected and investigated for adsorption of arsenate [As(V)]. Two kinetic models were used to describe the results of single solute batch adsorption experiments. Piecewise linear regression of data linearized to fit pseudo-first order kinetic model resulted in two distinct rates and a cutoff time point of 14–19 h delineating the biphasic behavior of solute adsorption. During the initial rapid adsorption stage, an average of 60–80% of the total adsorption took place. Pseudo-second order kinetic models provided the best fit to the experimental data (R2 > 0.99) and were capable of describing the adsorption over the entire range of experiments. Both Langmuir and Freundlich isotherms provided reasonable fits to the adsorption data at equilibrium. Langmuir-derived maximum adsorption capacity (St) of the studied sediments ranged between 29 and 97 mg/kg increasing from contaminated to uncontaminated sites. Solid phase As content of the sediments ranged from 3.8 to 10 mg/kg and the As/Fe ratios were highest in the amorphous phase. High-pH desorption experiments resulted in a greater percentage of solid phase As released into solution from experimentally-loaded sediments than from the unaltered samples suggesting that As(V) adsorption takes place on different reversible and irreversible surface sites.

Diel methane emission fluxes from a landfill that was covered by vegetation were investigated to reveal the methane emission mechanisms based on the interaction of vegetation characteristics and climate factors. The methane emissions showed large variation between daytime and nighttime, and the trend of methane emissions exhibited clear bimodal patterns from both Setaria viridis- and Neyraudia reynaudiana-covered areas. Plants play an important role in methane transportation as well as methane oxidation. The notable decrease in methane emissions after plants were cut suggests that methane transportation via plants is the primary way of methane emissions in the vegetated areas of landfill. Within plants, the methane emission fluxes were enhanced due to a convection mechanism. Given that the methane emission flux is highly correlated with the solar radiation during daytime, the convection mechanism could be attributed to the increase in solar radiation. Whereas the methane emission flux is affected by a combined impact of the wind speed and pedosphere characteristics during nighttime. An improved understanding of the methane emission mechanisms in vegetated landfills is expected to develop a reliable model for landfill methane emissions and to attenuate greenhouse gas emissions from landfills.

The concept of thresholds shows important implications for environmental and resource management. Here we derived potential landscape thresholds which indicated abrupt changes in water quality or the dividing points between exceeding and failing to meet national surface water quality standards for a rapidly urbanizing city on the Eastern Coast in China. The analysis of landscape thresholds was based on regression models linking each of the seven water quality variables to each of the six landscape metrics for this coupled land-water system. We found substantial and accelerating urban sprawl at the suburban areas between 2000 and 2008, and detected significant nonlinear relations between water quality and landscape pattern. This research demonstrated that a simple modeling technique could provide insights on environmental thresholds to support more-informed decision making in land use, water environmental and resilience management.

There is increasing controversy on whether acute exposure to ambient carbon monoxide (CO) is hazardous on respiratory health. We therefore performed a longitudinal panel study to evaluate the acute effects of ambient CO on fractional exhaled nitric oxide (FeNO), a well-established biomarker of airway inflammation. We completed 4–6 rounds of health examinations among 75 healthy young adults during April to June in 2013 in Shanghai, China. We applied the linear mixed-effect model to investigate the short-term associations between CO and FeNO. CO exposure during 2–72 h preceding health tests was significantly associated with decreased FeNO levels. For example, an interquartile range increase (0.3 mg/m³) of 2-h CO exposure corresponded to 10.6% decrease in FeNO. This association remained when controlling for the concomitant exposure to co-pollutants. This study provided support that short-term exposure to ambient CO might be related with reduced levels of FeNO, a biomarker of lower airway inflammation.

Low tech photovoltaic panels (PVPs) installed in the early ’80s are now coming to the end of their life cycle and this raises the problem of their proper disposal. As panels contain potentially toxic elements, unconventional, complex and costly procedures are required to avoid environmental health risks and in countries where environmental awareness and economic resources are limited this may be especially problematic. This work was designed to investigate potential risks from improper disposal of these panels. To accomplish this aim an exhausted panel was broken into pieces and these were placed in water for 30 days. The resulting leached solution was analyzed to determine chemical release or used in toto, to determine its potential toxicity in established tests. The end points were seed germination (on Cucumis sativus and Lens culinaris) and effects on early development in three larval models: two crustaceans, Daphnia magna and Artemia salina, and the sea urchin Paracentrotus lividus. Our results show that the panels release small amounts of electrolytes (Na, Ca and Mg) into solution, along with antimony and manganese, with a concentration under the accepted maximum contaminant level, and nickel at a potentially toxic concentration. Developmental defects are seen in the plant and animal test organisms after experimental exposure to the whole solution leached from the broken panel. The toxic effects revealed in in vitro tests are sufficient to attract attention considering that they are exerted on both plants and aquatic animals and that the number of old PVPs in disposal sites will be very high.

Colloids (non-biological and biological) with different sizes are ubiquitous in natural environment. The investigations regarding the influence of different-sized colloids on the transport and deposition behaviors of engineered-nanoparticles in porous media yet are still largely lacking. This study investigated the effects of different-sized non-biological and biological colloids on the transport of titanium dioxide nanoparticles (nTiO2) in quartz sand under both electrostatically favorable and unfavorable conditions. Fluorescent carboxylate-modified polystyrene latex microspheres (CML) with sizes of 0.2–2 μm were utilized as model non-biological colloids, while Gram-negative Escherichia coli (∼1 μm) and Gram-positive Bacillus subtilis (∼2 μm) were employed as model biological colloids. Under the examined solution conditions, both breakthrough curves and retained profiles of nTiO2 with different-sized CML particles/bacteria were similar as those without colloids under favorable conditions, indicating that the copresence of model colloids in suspensions had negligible effects on the transport and deposition of nTiO2 under favorable conditions. In contrast, higher breakthrough curves and lower retained profiles of nTiO2 with CML particles/bacteria relative to those without copresent colloids were observed under unfavorable conditions. Clearly, the copresence of model colloids increased the transport and decreased the deposition of nTiO2 in quartz sand under unfavorable conditions (solution conditions examined in present study). Both competition of deposition sites on quartz sand surfaces and the enhanced stability/dispersion of nTiO2 induced by copresent colloids were found to be responsible for the increased nTiO2 transport with colloids under unfavorable conditions. Moreover, the smallest colloids had the highest coverage on sand surface and most significant dispersion effect on nTiO2, resulting in the greatest nTiO2 transport.

Antifouling paint applied to fishing vessels is the primary source of dichloro-diphenyl-trichloroethane (DDT) to the coastal marine environments of China. With the aim to provide science-based support of potential regulations on DDT use in antifouling paint, we utilized a fugacity-based model to evaluate the fate and impact of p,p′-DDT, the dominant component of DDT mixture, in Daya Bay and Hailing Bay, two typical estuarine bays in South China. The emissions of p,p′-DDT from fishing vessels to the aquatic environments of Hailing Bay and Daya Bay were estimated as 9.3 and 7.7 kg yr−1, respectively. Uncertainty analysis indicated that the temporal variability of p,p′-DDT was well described by the model if fishing vessels were considered as the only direct source, i.e., fishing vessels should be the dominant source of p,p′-DDT in coastal bay areas of China. Estimated hazard quotients indicated that sediment in Hailing Bay posed high risk to the aquatic system, and it would take at least 21 years to reduce the hazards to a safe level. Moreover, p,p′-DDT tends to migrate from water to sediment in the entire Hailing Bay and Daya Bay. On the other hand, our previous research indicated that p,p′-DDT was more likely to migrate from sediment to water in the maricultured zones located in shallow waters of these two bays, where fishing vessels frequently remain. These findings suggest that relocating mariculture zones to deeper waters would reduce the likelihood of farmed fish contamination by p,p′-DDT.

Polycyclic aromatic hydrocarbons (PAHs) were studied in 230 daily fine particulate matter (PM2.5) samples collected in four seasons at urban and suburban sites of Shanghai, China. This study focused on the emission sources of PAHs and its dynamic results under different weather conditions and pollution levels and also emphasized on the spatial sources of PM2.5 and PAHs at a regional level. Annual concentrations of PM2.5 and 16 EPA priority PAHs were 53 μg/m3 and 6.9 ng/m3, respectively, with highest levels in winter. Positive matrix factorization (PMF) modeling identified four sources of PAHs: coal combustion, traffic, volatilization and biomass combustion, and coking, with contributions of 34.9%, 27.5%, 21.1% and 16.5%, respectively. The contribution of traffic, a local-indicative source, increased from 17.4% to 28.7% when wind speed changed from >2m/s to <2m/s, and increased from 18.3% to 31.3% when daily PAH concentrations changed from below to above the annual mean values. This indicated that local sources may have larger contributions under stagnant weather when poorer dispersion conditions and lower wind speed led to the accumulation of local-emitted pollutants. The trajectory clustering and potential source contribution function (PSCF) and concentration weighted trajectory (CWT) models showed clearly that air parcels moved from west had highest concentrations of PM2.5, total PAHs and high molecular weight (HMW) PAHs. While small differences were found among all five clusters in low molecular weight (LMW) PAHs. Sector analyses determined that regional transport source contributed 39.8% to annual PM2.5 and 52.5% to PAHs, mainly from western regions and varying with seasons. This work may make contribution to a better understanding and control of the increasingly severe air pollution in China as well as other developing Asian countries.

The quantification of atmospheric deposition flux is essential for assessment of its impact on ecosystems. We present an advanced approach for the estimation of the spatial pattern of atmospheric nitrogen deposition flux over the Czech forests, collating all available measured data and model results. The aim of the presented study is to provide an improved, more complete, more reliable and more realistic estimate of the spatial pattern of nitrogen deposition flux over one country. This has so far usually been based on measurements of ambient NOx concentrations as dry deposition proxy, and NH4+ and NO3− in precipitation as wet deposition proxy. For estimation of unmeasured species contributing to dry deposition, we used the CAMx Eulerian photochemical dispersion model, coupled with the Aladin regional numeric weather prediction model. The contribution of fog and dissolved organic nitrogen was estimated using a geostatistical data driven model. We prepared individual maps for particular components applying the most relevant approach and then merged all layers to obtain a final map representing the best estimate of nitrogen deposition over the Czech Republic. Final maps accounting for unmeasured species clearly indicate that the approach used so far may result in a substantial underestimation of nitrogen deposition flux. Our results showed that nitrogen deposition over the Czech forested area in 2008 was well above 2 g N m−2 yr−1, with almost 70% of forested area receiving 3–4 g N m−2 yr−1. NH3 and gaseous HNO3, contributing about 80%, dominated the dry nitrogen deposition. Estimating the unmeasured nitrogen species by modeled values provides realistic approximations of total nitrogen deposition that also result in more realistic spatial patterns that could be used as input for further studies of likely nitrogen impacts on ecosystems.

Increasing trace metal pollution in river sediment poses a significant threat to watershed ecosystem health. Identifying potential sources of sediment metals and apportioning their contributions are of key importance for proposing prevention and control strategies of river pollution. In this study, three advanced multivariate receptor models, factor analysis with nonnegative constraints (FA-NNC), positive matrix factorization (PMF), and multivariate curve resolution weighted-alternating least-squares (MCR-WALS), were comparatively employed for source apportionment of trace metals in river sediments and applied to the Le'an River, a main tributary of Poyang Lake which is the largest freshwater lake in China. The pollution assessment with contamination factor and geoaccumulation index suggested that the river sediments in Le'an River were contaminated severely by trace metals due to human activities. With the three apportionment tools, similar source profiles of trace metals in sediments were extracted. Especially, the MCR-WALS and PMF models produced essentially the same results. Comparatively speaking, the weighted schemes might give better solutions than the unweighted FA-NNC because the uncertainty information of environmental data was considered by PMF and MCR-WALS. Anthropogenic sources were apportioned as the most important pollution sources influencing the sediment metals in Le'an River with contributions of about 90%. Among them, copper tailings occupied the largest contribution (38.4–42.2%), followed by mining wastewater (29.0–33.5%), and agricultural activities (18.2–18.7%). To protect the ecosystem of Le'an River and Poyang Lake, special attention should be paid to the discharges of mining wastewater and the leachates of copper tailing ponds in that region.