This is the first study to characterize the variation and emission of C₂-C₅ non-methane volatile organic compounds (NMVOCs) in a semi-urban site of western India based on measurements during February–December 2015. Anthropogenic NMVOCs show clear seasonal dependence with highest in winter and lowest in monsoon season. Biogenic NMVOCs likes isoprene show highest mixing ratios in the pre-monsoon season. The diurnal variation of NMVOC species can be described by elevated values from night till morning and lower values in the afternoon hours. The elevated levels of NMVOCs during night and early morning hours were caused mainly by weaker winds, temperature inversion and reduced chemical loss. The correlations between NMVOCs, CO and NOx indicate the dominant role of various local emission sources. Use and leakage of liquefied petroleum gas (LPG) contributed to the elevated levels of propane and butanes. Mixing ratios of ethylene, propylene, CO, NOx, etc. show predominant emissions from combustion of fuels in automobiles and industries. The Positive Matrix Factorization (PMF) source apportionments were performed for the seven major emission sectors (i.e. Vehicular exhaust, Mixed industrial emissions, Biomass/Fired brick kilns/Bio-fuel, Petrochem, LPG, Gas evaporation, Biogenic). Emissions from vehicle exhaust and industry-related sources contributed to about 19% and 40% of the NMVOCs, respectively. And the rest (41%) was attributed to the emissions from biogenic sources, LPG, gasoline evaporation and biomass burning. Diurnal and seasonal variations of NMVOCs were controlled by local emissions, meteorology, OH concentrations, long-range transport and planetary boundary layer height. This study provides a good reference for framing environmental policies to improve the air quality in western region of India.

This study investigated bacterial diversities in surface water and sediment of the East Lake located in Wuhan, China. Bacterial community of lake water was mainly composed of Proteobacteria (31.1%), Actinobacteria (25.0%), Bacteroidetes (18.6%), Cyanobacteria (18.9%), Planctomycetes (2.4%) and Verrucomicrobia (1.4%), while more abundant and richer bacterial community was found in the sediments, e.g. 46.1% for Proteobacteria, 10.1% for Bacteroidetes, 8.7% for Chloroflexi, 8.4% for Acidobacteria, 5.0% for Cyanobacteria, 3.6% for Firmicutes, 3.1% for Planctomycetes, 2.8% for Actinobacteria and 2.3% for Nitrospirae. The decreased bacterial community richness and abundance was found in poor-quality water. Moreover, Bacterial Eutrophic Index (BEI) was firstly put forward to quantitatively describe the water quality of a freshwater ecosystem, which was defined as the ratio of abundance of Cyanobacteria and Actinobacteria in water. It was demonstrated BEI was well correlated to Carlson's Trophic State Index (TSI) (Spearman's ρ = 0.848, p < 0.01). The average TSI and BEI were determined to be 64 and 0.81, suggesting that East Lake could be classified as a medium eutrophic level.

Nitrogen is one of the most significant pollutants in the Yangtze River estuary (YRE), China. Reliable estimation of nitrogen concentration in the water is crucial for assessment of the water quality of the estuary. Because ocean fronts exist in the YRE, which divide water masses into different regions, it is necessary to account for the heterogeneity of the water surface when predicting nitrogen concentrations. A new geostatistical method, called spatiotemporal point mean of surface with non-homogeneity (ST-PMSN), is proposed to model the non-stationary spatiotemporal random process of nitrogen concentrations between 2004 and 2013 in the YRE. The method considers the spatiotemporal correlation of surface water nitrogen and uses information from both sides of a boundary for heterogeneous water masses. Comparing with several other interpolating methods, including spatial ordinary kriging (OK), stratified ordinary kriging (SOK), point mean of surface with non-homogeneity (P-MSN), spatiotemporal ordinary kriging (STK), and stratified spatiotemporal ordinary kriging (SSTK), the cross-validation results show that ST-PMSN has the highest accuracy, followed by SSTK, STK, P-MSN, SOK, and OK in descending order. ST-PMSN is therefore demonstrated to be effective in estimating the nitrogen pollutant concentrations in a stratified estuary. According to interpolated nitrogen concentrations in the YRE, water quality has generally deteriorated—with fluctuations—from 2004 to 2013. The average annual reduction in area of water quality of Grades I and II from 2004 to 2013 was 1.10%. At the same time, the average annual increase in area of water quality of Grades III and IV was 0.89% and that of Grade V was 0.21%. The results of this study provide a new and more accurate interpolating method for assessing the pollutant concentration in the marine and offers guidance for more precise classification of water quality in the YRE.

Dust samples were collected from four indoor environments, including childcare facilities, houses, hair salons, and a research facility from the USA and were analyzed for brominated compounds using full scan liquid chromatography high-resolution mass spectrometry. A total of 240 brominated compounds were detected in these dust samples, and elemental formulas were predicted for 120 more abundant ions. In addition to commonly detected brominated flame retardants (BFRs), nitrogen-containing brominated azo dyes (BADs) were among the most frequently detected and abundant. Specifically, greater abundances of BADs were detected in indoor dusts from daycares and salons compared to houses and the research facility. Using authentic standards, a quantitative method was established for two BADs (DB373: Disperse Blue 373 and DV93: Disperse Violet 93) and 2-bromo-4,6-dinitroaniline, a commonly used precursor in azo dye production, in indoor dust. Generally, greater concentrations of DB373 (≤3850 ng/g) and DV93 (≤1190 ng/g) were observed in indoor dust from daycares highlighting children as a susceptible population to potential health risk from exposure to BADs. These data are important because, to date, targeted analysis of brominated compounds in indoor environments has focused mainly on BFRs and appears to underestimate the total amount of brominated compounds.

Few studies have reported the association between greenspace and academic performance at school level. We examined associations between both residential and school greenspace and individual school grades in German adolescents.German and maths grades from the latest school certificate, residential and school greenspace, and covariates were available for 1351 10 and 15 years old Munich children and 1078 Wesel children from two German birth cohorts – GINIplus and LISA. Residential and school greenspace was assessed by the Normalized Difference Vegetation Index (NDVI), tree cover, and (in Munich only) proportion of agricultural land, forest, and urban green space in 500-m and 1000-m circular buffers. Longitudinal associations between each exposure-outcome pair were assessed by logistic mixed effects models with person and school as random intercepts and adjusted for potential confounders.No associations were observed between any of the greenspace variables and grades in Wesel children. Several statistically significant associations were observed with German and maths grades in Munich children, however associations were inconsistent across sensitivity analyses.There is no evidence of an association of higher greenspace at residence, school or combined with improved academic performance in German adolescents from the GINIplus and LISA longitudinal studies.

China has performed crop residue burning (CRB) for a long time and has suffered from resultant environmental pollution. High temporal resolution has not been fully discussed in attempts to address the temporal and spatial impact of CRB in China on air quality. Our study used the MOD14A1 product of the MODerate resolution Imaging Spectrometer (MODIS) to extract the daily CRB for China during the period from 2014 to 2016, and the daily aerosol optical depth (AOD) provided by MODIS Collection 6 was obtained to simultaneously reflect the air pollution. First, the study area was classified into five subregions. A temporal analysis was conducted on the daily variation in the number of CRB events and the regional mean value of AOD, the spatial contribution ratio of CRB on aerosol pollution was then calculated, and finally, a temporal and spatial Pearson correlation was calculated to find the spatially varying relationship between CRB and aerosol. The results suggest the following: (1) CRB possesses seasonal characteristics that are associated with the harvest time or sowing time of major crops in the region. (2) The impact of CRB on aerosol was delayed by 1–6 days. (3) High contribution ratios (70%–90%) occurred in northeast China on a large scale; even when the impact of the CRB on aerosol pollution in the Huang-Huai-Hai river basin occurred on a large scale, the value was merely approximately 30%. Relatively low contributions of CRB have been found in other places, whereas the contribution of CRB was severe in some places with high-density populations. (4) Temporal-spatial correlation provided an accurate index to reflect the correlation of CRB and aerosol in a specific location, which suggests that, in places with large scale and dense CRB, CRB tends to have a high positive correlation with aerosol pollution for each day.

We measured the concentrations of organophosphate esters (OPEs) in some biotic samples which can serve as human foodstuffs and ambient environments including air and river water from an agricultural area of Chongqing, western China. Fish samples exhibited highest OPEs levels (960 ng/g lipid weight) among the biota, followed by chicken (676 ng/g lw), cattle (545 ng/g lw) and pigs (535 ng/g lw). Tributyl phosphate (TNBP), tris (2-methylpropyl) (TIBP) and chlorinated OPEs were the major analogs in biotic samples, which appeared similar with the patterns from river water and outdoor air, but apparently different from indoor air. To further investigate the influence of ambient environment on the distribution of OPEs in biota, we analyzed the correlation between OPEs concentrations in ambient environment and biological samples, and the results revealed that most of the samples (except for pig samples) heavily correlated with outdoor air, whereas only fish and cattle samples were strongly correlated with river water. The partitioning behaviors of OPEs among biota, air and river water were also studied through calculating the biota-water accumulation factors (BWAFs), biota-air accumulation factors (BAAFs) and air-water partitioning factor (AWPFs). Significantly linear correlations (P < 0.05) were observed between log (BWAFs) and log (KOW) values, and between log (AWPFs) and log H (Henry's law constants), nevertheless log (BAAFs) was increasing along with the log (KOA) values. The daily intake (DI) values were estimated via foodstuffs ingestion and environmental exposure. The estimated DI values of OPEs from food and ambient environments were 1.78 ng/kg-bw/day, 1.23 ng/kg-bw/day and 1.42 ng/kg-bw/day in toddlers, children and adults, respectively, which lay at the low end of the reported data and well below the reference dose (RfD).

In this study, we carried out high time-resolution measurements of particle number concentration and size distribution (5–1000 nm) in Singapore, which represents a tropical urban environment. The measurements were taken during the southwest monsoon season in 2017 using a fast-response differential mobility spectrometer at a sampling rate of 1 Hz. In the measurement, short-lived nucleation events were found prominent at early afternoon because of the abundant incoming radiation that enhances the photochemical reactions in atmosphere. For the first time in the region, a five-factor positive matrix factorization approach was applied to the size spectra data. Based on particle number concentration, two sources within nucleation mode (<30 nm) were resolved and account for 43% of total number concentration, which is higher than the available monitoring data in other big cities. Among the sources, O₃-related atmospheric photochemical reactions with peak size at 10–12 nm is a unique factor and prominent in early afternoon nucleation events. The findings of this work can serve as a baseline for assessing influence of local and cross-border airborne emissions during various seasons in the future.

Exposure to phthalates is reported to be associated with increased incidence of microalbuminuria and low-grade albuminuria in children and adolescents. However, this phenomenon of phthalate-related nephrotoxicity is unknown in adults.Urine samples of 1663 adults from the 2012 Shanghai Food Consumption Survey (SHFCS) were measured for 10 metabolites of 6 phthalates and for renal function parameters. Their associations were explored by linear and logistic regression models.Multivariate linear regression analysis showed that all three renal function parameters (albumin-to-creatinine ratio (ACR), β2-microglobulin (B2M), and N-acetyl-β-d-glucosaminidase (NAG)) are positively associated with six metabolites, including mono-benzylphthalate (MBzP), mono-2-ethylhexylphthalate (MEHP), mono-2-ethyl-5-oxohexyphthalate (MEOHP), mono-2-ethyl-5-hydroxyhexylphthalate (MEHHP), mono-2-ethyl-5-carboxypentylphthalate (MECPP), and mono-2-carboxymethyl-hexyl phthalate (MCMHP) (P < 0.05). Logistic analysis showed that the prevalence of hyperALBuria, hyperB2Muria, hyperNAGuria, or potentially impaired renal function (PIRF) were positively associated with urinary levels of MBzP, MEOHP, and MECPP, respectively (P < 0.05). Co-exposure to identified risk metabolites monoethylphthalate (MEP), MBzP, MEHP, MEOHP, MECPP, MEHHP, and MCMHP increased the risk of having impaired renal function.Certain metabolites of phthalates, including bis (2-ethylhexyl) phthalate (DEHP) and benzyle butyl phthalate (BBzP), were associated with impaired renal function in Shanghai adults.

Based on long-term systematic sampling, information is currently limited regarding the impacts of different air pollution levels on variations of bacteria, fungi and ammonia-oxidizing microorganisms (AOMs) in fine particulate matter (PM₂.₅), especially their interactions. Here, PM₂.₅ samples were weekly collected at different air pollution levels in Beijing, China during one-year period. Microbial composition was profiled using Illumina sequencing, and their interactions were further investigated to reveal the hub genera with network analysis. Diversity of bacteria and fungi showed obvious seasonal variations, and the heavy- or severe-pollution levels mainly affected the diversity and composition of bacteria, but not fungi. While, the community structure of both bacteria and fungi was influenced by the combination of air pollution levels and seasons. The most abundant bacterial genera and some genera with highest abundance in heavy- or severe-pollution days were the hub bacteria in PM₂.₅. Whereas, only the dominant fungi in light-pollution days in winter were the hub fungi in PM₂.₅. The complex positive correlations of bacterial or fungal pathogens would aggravate the air pollution effects on human health, despite of their low relative abundances. Moreover, the strong co-occurrence and co-exclusion patterns of bacteria and fungi in PM₂.₅ were identified. Furthermore, the hub environmental factors (e.g., relative humidity and atmospheric pressure) may play central roles in the distributions of bacteria and fungi, including pathogens. Importantly, AOMs showed significant co-occurrence patterns with the main bacterial and fungal genera and potential pathogens, providing possible microbiological evidences for controlling ammonia emissions to effectively reduce PM₂.₅ pollution. These results highlighted the more obvious air pollution impacts on bacteria than fungi, and the complex bacterial-fungal interactions, as well as the important roles of AOMs in airborne microbial interactions webs, improving our understanding of bioaerosols in PM₂.₅.