Satellite-retrieved aerosol optical depth (AOD) is commonly used to estimate ambient levels of fine particulate matter (PM₂.₅), though it is important to mitigate the estimation bias of PM₂.₅ due to gaps in satellite-retrieved AOD. A nonparametric approach with two random-forest submodels is proposed to estimate PM₂.₅ levels by filling gaps in satellite-retrieved AOD. This novel approach was employed to estimate the spatiotemporal distribution of daily PM₂.₅ levels during 2013–2015 in the Sichuan Basin of Southwest China, where the coverage rate of composite AOD retrieved by the Terra and Aqua satellites was only 11.7%. Based on the retrieved AOD and various covariates (including meteorological conditions and land use types), the first random-forest submodel (named AOD-submodel) was trained to fill the gaps in the AOD dataset, giving a cross-validation R² of 0.95. Subsequently, the second random-forest submodel (named PM₂.₅-submodel) was trained to estimate the PM₂.₅ levels for unmonitored areas/days based on the gap-filled AOD, ground-monitored PM₂.₅ levels, and the covariates, and achieved a cross-validation R² of 0.86. By comparing the complete and incomplete (i.e., without the days when AOD data were missing) estimates, we found that the monthly PM₂.₅ levels could be overestimated by 34.6% if the PM₂.₅ values coincident with AOD gaps were not considered. The newly developed approach is valuable for deriving the complete spatiotemporal distribution of daily PM₂.₅ from incomplete remote-sensing data, which is essential for air quality management and human exposure assessment.

Colloids are ubiquitous in soils, and it has been reported that colloids can act as carriers to increase the mobility of poorly soluble contaminants in subsurface environments. Addition of sulfur (S) fertilizer greatly influences on heavy metal behavior in paddy soil, while the influence of S fertilizer on Cu migration and transformation in colloids of soil pore water has not yet been studied. The influence of S fertilizer (S⁰ and Na₂SO₄) applied in paddy soils on Cu migration and transformation in colloids of soil pore water from the rice rhizosphere region was explored in this study. The speciation of Cu in colloids of soil pore water from the rice rhizosphere region was explored by advanced synchrotron-based X-ray absorption near-edge spectroscopy (XANES) techniques. The morphology of colloids was characterized by field emission scanning electron microscopy coupled to energy dispersive X-ray spectroscopy (SEM-EDX). At a depth of 20 cm, the concentration of Cu in colloids of the rhizosphere soil pore water in the control was 2.4- and 6.5- fold higher than that in treatments of S⁰ and Na₂SO₄, respectively. The colloids in soil pore water were all positively charged, ranging from 2.4 to 7.8 mV, and the size of colloids was 440–740 nm. The proportion of Fe in colloids in the rhizosphere region decreased with S fertilizer application, while the proportions of C and O increased. Sulfur fertilizer application, increased the proportion of Cu-Cysteine, while the proportion of Cu₂S decreased in soil colloids. In conclusion, application of sulfur fertilizer in paddy soil decreased the Cu concentration in soil pore water and colloids of the rhizosphere region, thereby decreasing the vertical migration of Cu in soil pore water.

Temuco is a mid-size city representative of severe wood smoke pollution in southern Chile; however, little is known about the indoor air quality in this region. A field measurement campaign at 63 households in the Temuco urban area was conducted in winter 2014 and is reported here. In this study, indoor and outdoor (24-hr) PM2.5 and its elemental composition were measured and compared. Infiltration parameters and outdoor/indoor contributions to indoor PM2.5 were also determined. A statistical evaluation of how various air quality interventions and household features influence indoor PM2.5 was also performed.This study determined median indoor and outdoor PM2.5 concentrations of 44.4 and 41.8 μg/m3, respectively. An average infiltration factor (0.62 ± 0.06) was estimated using sulfur as a tracer species. Using a simple mass balance approach, median indoor and outdoor contributions to indoor PM2.5 concentrations were then estimated as 12.5 and 26.5 μg/m3, respectively; therefore, 68% of indoor PM2.5 comes from outdoor infiltration. This high percentage is due to high outdoor pollution and relatively high household air exchange rates (median: 1.06 h−1).This study found that S, Br and Rb were dominated by outdoor contributions, while Si, Ca, Ti, Fe and As originated from indoor sources. Using continuous indoor and outdoor PM2.5 measurements, a median indoor source strength of 75 μg PM2.5/min was estimated for the diurnal period, similar to literature results. For the evening period, the median estimate rose to 135 μg PM2.5/min, reflecting a more intense wood burning associated to cooking and space heating at night.Statistical test results (at the 90% confidence level) support the ongoing woodstove replacement program (reducing emissions) and household weatherization subsidies (reducing heating demand) for improving indoor air quality in southern Chile, and suggest that a cookstove improvement program might be helpful as well.

To improve the accuracy and temporal-spatial resolution for a vehicle emission inventory in a medium-sized city with a strip road network, this study was conducted based on detailed hourly traffic-flow data for each day of 2014, and covered all road types and regions in the city of Foshan. Detailed hourly emission characteristics and sources in five regions were analysed. The results showed that the total vehicle emissions of CO, NOX, VOCs, and PM2.5 were 13.10 × 104, 0.23 × 104, 4.46 × 104, and 0.18 × 104 tons, respectively. Motorcycles (MCs) and light passenger cars (LPCs) were the dominant contributors of CO emissions, while buses and heavy passenger cars (HPCs) were the dominant contributors for NOX. As a whole, the daytime contributions to total emissions were close to 80%, and emissions during the peak periods accounted for almost 40%. Specifically, the hourly emissions of each pollutant on workdays were higher than on non-workdays (maximum up to 64.2%), and for some roads the early peak periods changed significantly from workdays to non-workdays. At expressways, artery roads, and local roads, the daily emission intensities of CO, NOx, and PM2.5 in Foshan were close to or even higher than that of Beijing. On a regional scale, the temporal variation of vehicle emissions on workdays at artery roads of different regions were similar. In addition, the higher emission intensities of CO and VOCs were identified in DaLiang-RongGui (DLRG) and that of NOX and PM2.5 were in Central Region (CR). These results are meaningful for decision-makers to help provide more detailed vehicle pollution control measures in Foshan with a strip road network and only one ring road.

Chemical mass balance (CMB) modeling and radiocarbon measurements were combined to evaluate the sources of carbonaceous fine particulate matter (PM2.5) in Shenzhen, China during and after the 2011 summer Universiade games when air pollution control measurements were implemented to achieve air quality targets. Ambient PM2.5 filter samples were collected daily at two sampling sites (Peking University Shenzhen campus and Longgang) over 24 consecutive days, covering the controlled and uncontrolled periods. During the controlled period, the average PM2.5 concentration was less than half of what it was after the controls were lifted. Organic carbon (OC), organic molecular markers (e.g., levoglucosan, hopanes, polycyclic aromatic hydrocarbons), and secondary organic carbon (SOC) tracers were all significantly lower during the controlled period. After pollution controls ended, at Peking University, OC source contributions included gasoline and diesel engines (24%), coal combustion (6%), biomass burning (12.2%), vegetative detritus (2%), biogenic SOC (from isoprene, α-pinene, and β-caryophyllene; 7.1%), aromatic SOC (23%), and other sources not included in the model (25%). At Longgang after the controls ended, similar source contributions were observed: gasoline and diesel engines (23%), coal combustion (7%), biomass burning (17.7%), vegetative detritus (1%), biogenic SOC (from isoprene, α-pinene, and β-caryophyllene; 5.3%), aromatic SOC (13%), and other sources (33%). The contributions of the following sources were smaller during the pollution controls: biogenic SOC (by a factor of 10–16), aromatic SOC (4–12), coal combustion (1.5–6.8), and biomass burning (2.3–4.9). CMB model results and radiocarbon measurements both indicated that fossil carbon dominated over modern carbon, regardless of pollution controls. However, the CMB model needs further improvement to apportion contemporary carbon (i.e. biomass burning, biogenic SOC) in this region. This work defines the major contributors to carbonaceous PM2.5 in Shenzhen and demonstrates that control measures for primary emissions could significantly reduce secondary organic aerosol (SOA) formation.

At the Pearl River Estuary of southern China, mercury and its environmental problems have long been a great concern. This study investigated the distribution and speciation of mercury compounds that are significantly influenced by the increasing content of humic acid (HA, a model natural organic matter) in this region. The inorganic mercury and methyl mercury, being adsorbed and converted at different HA levels, were studied in sediments and surface water at both mariculture and their reference sites. In mariculture sediments with higher HA content (up to 4.5%), more mercury were adsorbed at different compound levels, promoting the methylation and accumulation of mercury (P < 0.05) at the sediment-water interface. Seasonal shift in environmental temperature might control the HA content, subsequently favouring mercury methylation (maximum 1.75 ± 0.08 mg L−1 d−1) under warm weather conditions. In reference sites received less HA wastes, lower adsorption capacity and methylation rate were observed for mercury in sediments and surface water. Our work points to the significant roles of HA on mercury distribution and speciation both spatially and seasonally, thus addressing the impacts of mariculture activities on estuary eco-system.

Pulse diffusive nitrous oxide (N₂O) emission following water application is well documented, whereas N₂O emission caused by soil water-air displacement during the watering process (termed as soil degassing) has been largely overlooked. Watering-induced N₂O emissions from ten different soils in China were quantified, and found to range from 74.4 ± 6.7 to 678.1 ± 36.6 μg N₂O m⁻² h⁻¹ in surface watered (SW) soils, and from 45.6 ± 4.4 to 358.1 ± 23.6 μg N₂O m⁻² h⁻¹ in subsurface watered (SUW) soils. These N₂O fluxes were much larger than the diffusive N₂O flux from the same soil either under dry (7.9%–9.6% water filled pore space, WFPS) or wet (85.1%–93.6% WFPS) conditions. The watering process (the water infiltration process upon irrigation/rainfall or the process of shallow groundwater uplifting) resulted in massive N₂O emissions.

Exposure to pesticides results in DNA damage and genomic instability. We previously predicted that endosulfan might be associated with leukemia, but the role of endosulfan in leukemia cells has been unexplored. The aim of this study is to elucidate molecular mechanism of endosulfan-induced DNA damage response in human leukemia cells. We performed endosulfan exposure experiments in K562 cells with varying concentrations of endosulfan for 48 h and found that endosulfan lowered cell viability in a dose-dependent manner. We observed the dramatic DNA damage using comet assay and the increase of micronucleus in 75 μM endosulfan-exposed cells. Endosulfan at 75 μM caused the expression alterations of ATM and DNA repair genes such as FANCD2, and BRCA1/2 at different exposure time points (12, 24, 48 h), which was reversed by ATM inhibitor KU-55933. Endosulfan significantly increased the mRNA expression levels of p53 and GADD45A, and decreased PCNA and XRCC2 at 48 h after exposure. Flow cytometric analysis showed that endosulfan at 50 and 75 μM induced cell cycle G1 arrest, a response attributed to down-regulation of CDK6 and up-regulation of p21. We also observed that endosulfan at 50 and 75 μM induced a considerable percentage of cells to undergo apoptosis, as detected by Annexin-V binding assays. Endosulfan resulted in the activation of caspase-3, and elevated the expression levels of PUMA and the ratio of BAX/Bcl-2. These findings suggest that endosulfan caused DNA damage response throughATM-p53 signaling pathway, implicating the potential correlation between endosulfan and leukemia.

Pharmaceuticals have been considered ‘contaminants of emerging concern’ for more than 20 years. In that time, many laboratory studies have sought to identify hazard and assess risk in the aquatic environment, whilst field studies have searched for targeted candidates and occurrence trends using advanced analytical techniques. However, a lack of a systematic approach to the detection and quantification of pharmaceuticals has provided a fragmented literature of serendipitous approaches. Evaluation of the extent of the risk for the plethora of human and veterinary pharmaceuticals available requires the reliable measurement of trace levels of contaminants across different environmental compartments (water, sediment, biota - of which biota has been largely neglected). The focus on pharmaceutical concentrations in surface waters and other exposure media have therefore limited both the characterisation of the exposome in aquatic wildlife and the understanding of cause and effect relationships. Here, we compile the current analytical approaches and available occurrence and accumulation data in biota to review the current state of research in the field. Our analysis provides evidence in support of the ‘Matthew Effect’ and raises critical questions about the use of targeted analyte lists for biomonitoring. We provide six recommendations to stimulate and improve future research avenues.

During the last years, declines in honey bee colonies are being registered worldwide. Cholinergic pesticides and their extensive use have been correlated to the decline of pollinators and there is evidence that pesticides act as neuroendocrine disruptors affecting the metabolism of neuropeptides. However, there is a big absence of studies with quantitative results correlating the effect of pesticide exposure with changes on neuropeptides insects, and most of them are conducted under laboratory conditions, typically with individual active ingredients. In this study, we present an analytical workflow to evaluate pesticide effects on honey bees through the analysis of (neuro)peptides. The workflow consists of a rapid extraction method and liquid chromatography with triple quadrupole for preselected neuropeptides. For non-target analysis, high resolution mass spectrometry, multivariate analysis and automatic identification of discriminated peptides using a specific software and protein sequence databases. The analytical method was applied to the analysis of target and non-target (neuro)peptides in honey bees with low and high content of a wide range of pesticides to which have been exposed in field conditions. Our findings show that the identification frequency of target neuropeptides decreases significantly in honey bees with high concentration of pesticides (pesticide concentrations ≥ 500 μg kg⁻¹) in comparison with the honey bees with low content of pesticides (pesticide concentrations ≤ 20 μg kg⁻¹). Moreover, the principal component analysis in non-target search shows a clear distinction between peptide concentration in honey bees with high level of pesticides and honey bees with low level. The use of high resolution mass spectrometry has allowed the identification of 25 non-redundant peptides responsible for discrimination between the two groups, derived from 18 precursor proteins.