Tree bark is considered as an effective passive sampler for estimating the atmospheric status of pollutants. In this study, we conducted a national scale tree bark sampling campaign across China. Concentration profiles revealed that Eastern China, especially the Jing-Jin-Ji region (including Hebei Province, Beijing and Tianjin) was a hot spot of bark DDT pollution. The enantioselective accumulation of o,p’-DDT was observed in most of the samples and 68% of them showed a preferential depletion of (+)-o,p’-DDT. These results suggest that DDTs in rural bark are likely from combined sources including historical technical DDTs and fresh dicofol usage. The tree bulk DDT levels were found to correlate with soil DDT concentrations, socioeconomy and PM2.5 of the sampling sites. It thus becomes evident that the reemission from soils and subsequent atmospheric deposition were the major pathways leading to the accumulation of DDTs in bark. Based on a previously established bark-air partitioning model, the concentrations of DDTs in the air were estimated from measured concentrations in tree bark, and the results were comparable to those obtained by the use of passive sampling with polyurethane foam (PUF) disks. Our results demonstrate the feasibility of delineating the spatial variations in atmospheric concentration and tracing sources of DDTs by integrating the use of tree bark with enantiomeric analysis.

A nationwide emission estimate of perfluoroalkyl substances (PFASs) from wastewater treatment plants (WWTPs) is required to understand the source–receptor relationship of PFASs and to manage major types of WWTPs. In this study, the concentrations of 13 PFASs (8 perfluorocarboxylic acids, 3 perfluoroalkane sulfonates, and 2 intermediates) in wastewater and sludge from 81 WWTPs in South Korea were collected. The emission pathways of PFASs were redefined, and then the national emission of PFASs from WWTPs was rigorously updated. In addition to the direct calculations, Monte Carlo simulations were also used to calculate the likely range of PFAS emissions. The total (Σ13PFAS) emission (wastewater + sludge) calculated from the direct calculation with mean concentrations was 4.03 ton/y. The emissions of perfluorooctanoic acid (PFOA, 1.19 ton/y) and perfluorooctane sulfonate (PFOS, 1.01 ton/y) were dominant. The Monte Carlo simulations suggested that the realistic national emission of Σ13PFASs is between 2 ton/y and 20 ton/y. Combined WWTPs treating municipal wastewater from residential and commercial areas were identified as a major emission source, contributing 65% to the total PFAS emissions. The Han and Nakdong Rivers were the primary contaminated rivers, receiving 89% of the total PFAS discharge from WWTPs. The results and methodologies in this study can be useful to establish a management policy for PFASs.

Fine particulate matter (PM2.5) air pollution outbreaks have recently occurred frequently in China. However, evidence of the associations between short-term exposure to PM2.5 and cardiovascular morbidity is still limited in China. This study aimed to evaluate the associations between PM2.5 and hospital emergency room visits (ERVs) for cardiovascular diseases in urban areas in Beijing. Daily counts of cardiovascular ERVs were collected from ten large general hospitals from Jan 1 to Dec 31, 2013. Air pollution data were obtained from the Beijing Environmental Protection Bureau including 17 monitoring stations. A generalized additive Poisson model was used to examine the associations between PM2.5 and cardiovascular ERVs after controlling for seasonality, day of the week, public holidays, influenza outbreaks, and weather conditions. In total, there were 56,221 cardiovascular ERVs during the study period. The daily mean PM2.5 concentration was 102.1 μg/m³, ranging from 6.7 μg/m³ to 508.5 μg/m³. Per 10 μg/m³ increase in PM2.5 was associated with a 0.14% (95% confidence interval [CI]: 0.01%–0.27%) increase in cardiovascular ERVs at lag3. Cumulative delayed estimates were greatest at lag0–5 (0.30%, 95% CI: 0.09%–0.52%). The estimates of percentage change in daily ERVs per 10 μg/m³ increase in PM2.5 were 0.56% (95%CI: 0.16%–0.95%) for ischemic heart disease (IHD) at lag0–1, 0.81% (95%CI: 0.05%–1.57%) for heart rhythm disturbances (HRD) at lag0–1 and 1.21% (95%CI: 0.27%–2.15%) for heart failure (HF) at lag0, respectively. The effects of PM2.5 on IHD ERVs during high temperature days (>11.01 °C) were significantly higher than that on low temperature days (≤11.01 °C) at lag0, lag0–1, lag0–3 and lag0–5 (P < 0.05). The study suggests that PM2.5 has acute impacts on cardiovascular ERVs in Beijing, especially on IHD, HRD and HF. The effects of PM2.5 on IHD ERVs vary by temperature.

Wet deposition is not only a mechanism for removing atmospheric pollutants, but also a process which reflects loadings of atmospheric pollutants. Our previous study on wet deposition examined the effectiveness of short-term control measures on atmospheric particulate pollution, which were partly effective for organic pollutants of current input sources. In the present study, dichlorodiphenyltrichloroethanes (DDTs) and hexachlorocyclohexanes (HCHs), representative of legacy contaminants, were measured in the same samples collected throughout the entire year of 2010 in Guangzhou, a large urban center in South China. Concentrations of ∑DDT (sum of o,p′ and p,p′-DDT, o,p′ and p,p′-DDE, o,p′ and p,p′-DDD, and p,p′-DDMU) and ∑HCH (sum of α-, β-, γ-, and δ-HCH) in wet deposition were in the ranges of nd–69 (average: 1.8 ng L−1) and nd–150 ng L−1 (average: 5.1 ng L−1), respectively. In addition, the results of source diagnostics and backward air mass trajectories appeared to suggest the transport of antifouling paint derived DDTs from the coastal region off South China to Guangzhou. The combined wet and dry deposition flux of ∑HCH in the first quarter (January to March) was greater than that in the fourth quarter (October to December), while those of ∑DDT were comparable in the first and fourth quarters. Similar trends were also observed for the concentrations of ∑HCH and ∑DDT in aerosol samples. These results suggested the short-term pollution control measures implemented during the 16th Asian Games and 10th Asian Para Games (held in November and December 2010, respectively) did not work well for DDTs. The reduced input of HCHs during the fourth quarter was probably associated with the strict ban on lindane for food safety, which also exposed the weakness of control measures focusing mainly on the removal of atmospheric particulate matter.

As a common source of environmental noise in China and many developing countries worldwide, construction work provokes many complaints and deterioration in acoustic climate quality. This paper describes research to obtain an improved understanding of people's community response to, and evaluation of, construction noise in three central cities of Zhejiang province, China. This involved carrying out a social survey using standard questionnaires developed by the International Commission on Biological Effects of Noise (ICBEN). A dose-response relationship model is established using a quadratic polynomial regression analysis based on construction noise exposure measurements from 40 construction sites in Hangzhou, Ningbo and Wenzhou.The results of the study indicate that the majority of people have a negative attitude to construction noise; the noise ranges between 60 dB and 80 dB (compared with 50 dB–70 dB traffic noise in Tianjin), with the percentage of highly annoyed people affected increasing from 15%-20% to 30%–40% over the range. There also different levels of annoyance depending on the time of day, and the location and activities of those affected. Other cultural differences are also apparent both between Ningbo/Wenzhou and the more urbane citizens of Hangzhou, and the Chinese people and their more noise-tolerant EU and Vietnam counterparts.The findings of this study provide a new perspective for the study of construction noise that can help local governments have an improved understanding of how residents react to construction noise for the purpose of selecting construction noise-mitigation projects and introducing construction noise-control regulations.

The complaints arising from the problem of odorants released by composting plants may impede the construction of new composting facilities, preclude the proper activity of existing facilities or even lead to their closure, with negative implications for waste management and local economy. Improving the knowledge on VOC emissions from composting processes is of particular importance since different VOCs imply different odour impacts. To this purpose, three different organic matrices were studied in this work: dewatered sewage sludge (M1), digested organic fraction of municipal solid waste (M2) and untreated food waste (M3). The three matrices were aerobically biodegraded in a bench-scale bioreactor simulating composting conditions. A homemade device sampled the process air from each treatment at defined time intervals. The samples were analysed for VOC detection. The information on the concentrations of the detected VOCs was combined with the VOC-specific odour thresholds to estimate the relative weight of each biodegraded matrix in terms of odour impact. When the odour formation was at its maximum, the waste gas from the composting of M3 showed a total odour concentration about 60 and 15,000 times higher than those resulting from the composting of M1 and M2, respectively. Ethyl isovalerate showed the highest contribution to the total odour concentration (>99%). Terpenes (α-pinene, β-pinene, p-cymene and limonene) were abundantly present in M2 and M3, while sulphides (dimethyl sulphide and dimethyl disulphide) were the dominant components of M1.

While considerable attention has been given to the measurement of mercury (Hg) and lead (Pb) concentrations and accumulation in detailed peat cores in central Canada, the geographic distribution and density of sampling are generally limited. Here, we use the Ontario Peatland Inventory to examine broad patterns of Hg and Pb concentration with depth, based on 338 peat cores (containing >1500 analyzed samples) from 127 bogs, fens and swamps located in southeastern, northeastern and northwestern sections of Ontario. Overall, Hg concentrations averaged 0.05 μg g⁻¹ and that of Pb averaged 10.8 μg g⁻¹. Maximum values in the top 50 cm of the profiles are 0.08 μg g⁻¹ and 26.2 μg g⁻¹ for Hg and Pb, respectively. The ratio between these values (surface) and the values from below 100 cm (background), where peat likely accumulated before 1850 and industrial activities were limited, are 2.3 and 6.6 for Hg and Pb, respectively. The highest surface:background concentration ratios are generally found in the westernmost part of the province and in the southeast for Hg and around areas that are more heavily populated for Pb. Our results show that a vast amount of Hg and Pb are stored in Ontarian peatlands, although the spatial distribution of these stores varies. The rapid decomposition of peat in a changing climate could release these pollutants to the atmosphere.

Toxicity and uptake of nano-CeO2 (nCeO2) in edible vegetables are not yet fully understood. In the present study, we grew romaine lettuce in sand amended with nCeO2. At high concentrations (1000 and 2000 mg/kg), nCeO2 diminished the chlorophyll content by 16.5% and 25.8%, respectively, and significantly inhibited the biomass production. nCeO2 (≥100 mg/kg) altered antioxidant enzymatic activities and malondialdehyde levels in the plants. nCeO2 (≥500 mg/kg) triggered a remarkable increase of nitrate-N level in the shoots, which can be converted to toxic nitrite in humans thereby posed risk to human health. Concentration dependent accumulation of Ce in the plant tissues was observed. X ray absorption near edge spectroscopy (XANES) results indicate that Ce presented as nCeO2 and CePO4 in the roots while as nCeO2 and Ce carboxylates in the shoots. Chelation of Ce3+ by citric acid or precipitation of Ce3+ by PO43− reduced the translocation and toxicity of nCeO2, indicating that release of Ce3+ played a critical role in the toxicity nCeO2.