Exposure to ambient fine particular matter (PM2.5) are linked to an increased risk of metabolic disorders, leading to enhanced rate of many diseases, such as inflammatory bowel disease (IBD), cardiovascular diseases, and pulmonary diseases; nevertheless, the underlying mechanisms remain poorly understood. In this study, BALB/c mice were exposed to filtered air (FA) or concentrated ambient PM2.5 (CPM) for 2 months using a versatile aerosol concentration enrichment system(VACES). We found subchronic CPM exposure caused significant lung and intestinal damage, as well as systemic inflammatory reactions. In addition, serum and BALFs (bronchoalveolar lavage fluids) metabolites involved in many metabolic pathways in the CPM exposed mice were markedly disrupted upon PM2.5 exposure. Five metabolites (glutamate, glutamine, formate, pyruvate and lactate) with excellent discriminatory power (AUC = 1, p < 0.001) were identified to predict PM2.5 exposure related toxicities. Furthermore, subchronic exposure to CPM not only significantly decreased the richness and composition of the gut microbiota, but also the lung microbiota. Strong associations were found between several gut and lung bacterial flora changes and systemic metabolic abnormalities. Our study showed exposure to ambient PM2.5 not only caused dysbiosis in the gut and lung, but also significant systemic and local metabolic alterations. Alterations in gut and lung microbiota were strongly correlated with metabolic abnormalities. Our study suggests potential roles of gut and lung microbiota in PM2.5 caused metabolic disorders.

Nitric oxide (NO) and hydrogen sulfide (H₂S) since their discovery have proven to be game changing molecules in alleviating abiotic stress. They individually play role in plant stress management while the pathways of stress regulation through their crosstalk remain elusive. The current study focuses on investigating the interplay of NO and H₂S signalling in the amelioration of arsenate As(V) toxicity in rice seedlings and managing its growth, photosynthesis, sucrose and proline metabolism. Results show that As(V) exposure declined fresh weight (biomass) due to induced cell death in root tips. Moreover, a diminished RuBisCO activity, decline in starch content with high proline dehydrogenase activity and increased total soluble sugars content was observed which further intensified in the presence of Nω-nitro-L-arginine methyl ester hydrochloride (L-NAME, an inhibitor of nitric oxide synthase-like activity), and DL-propargylglycine (PAG, an inhibitor of cysteine desulfhydrase activity). These results correlate with lower endogenous level of NO and H₂S. Addition of L-NAME increased As(V) toxicity. Interestingly, addition of SNP reverses effect of L-NAME suggesting that endogenous NO has a role in mitigating As(V) toxicity. Similarly, exogenous H₂S also significantly alleviated As(V) stress, while PAG further stimulated As(V) toxicity. Furthermore, application of H₂S in the presence of L – NAME and NO in the presence of PAG could still mitigate As(V) toxicity, suggesting that endogenous NO and H₂S could independently mitigate As(V) stress.

The space-borne measured fine-mode aerosol optical depth (fAOD) is a gross index of column-integrated anthropogenic particulate pollutants, especially over the populated land. The fAOD is the product of the AOD and the fine-mode fraction (FMF). While there exist numerous global AOD products derived from many different satellite sensors, there have been much fewer, if any, global FMF products with a quality good enough to understand their spatiotemporal variations. This is key to understanding the global distribution and spatiotemporal variations of air pollutants, as well as their impacts on global environmental and climate changes. Modifying our newly developed retrieval algorithm to the latest global-scale Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol product (Collection 6.1), a global 10-year FMF product is generated and analyzed here. We first validate the product through comparisons with the FMF derived from Aerosol Robotic Network (AERONET) measurements. Among our 169,313 samples, the satellite-derived FMFs agreed with the AERONET spectral deconvolution algorithm (SDA)-retrieved FMFs with a root-mean-square error (RMSE) of 0.22. Analyzed using this new product are the global patterns and interannual and seasonal variations of the FMF over land. In general, the FMF is large (>0.80) over Mexico, Myanmar, Laos, southern China, and Africa and less than 0.5 in the Sahelian and Sudanian zones of northern Africa. Seasonally, higher FMF values occur in summer and autumn. The linear trend in the satellite-derived and AERONET FMFs for different countries was explored. The upward trend in the FMFs was particularly strong over Australia since 2008. This study provides a new global view of changes in FMFs using a new satellite product that could help improve our understanding of air pollution around the world.

Nitrated polycyclic aromatic hydrocarbons (nitro-PAHs) have been widely studied for their mutagenic and carcinogenic effects. This study aims to investigate whether exposure to nitro-PAHs is associated with biomarkers of carbohydrate metabolism, an underlying risk factor for metabolic disorder. Early morning urine and blood samples were longitudinally collected two times with a four-week interval from 43 healthy adults. Five urinary amino-PAHs (1-aminonaphthalene, 2-aminonaphthalene, 9-aminophenanthrene, 2-aminofluorene, and 1-aminopyrene) were measured as biomarkers of nitro-PAH exposures. We measured plasma concentrations of glucose and six amino acids that can regulate insulin secretion, including aspartate (Asp), glutamate (Glu), glutamine (Gln), alanine (Ala), Arginine (Arg), and ornithine (Orn). We found that increasing concentrations of 9-aminophenanthrene were significantly associated with increasing glucose levels and with decreasing Asp, Glu, Ala, and Orn levels. We estimated that 26.4 %–43.8 % of the 9-aminophenanthrene-associated increase in glucose level was mediated by Asp, Glu, and Orn. These results suggest that exposure to certain nitro-PAHs affects glucose homeostasis, partly resulting from the depletion of insulin-stimulating amino acids (Asp, Glu, and Orn).

Conventional factor analyses can present problems in cases with changing numbers of sources and/or time-dependent source compositions. There is also lack of a reliable method to estimate uncertainties in the source contributions derived by positive matrix factorization (PMF). Applying a moving window evolving PMF to hourly PM₂.₅ composition dataset from a field campaign in Tianjin China that included the Spring and Lantern Festivals and the start of COVID-19 pandemic has substantially improved the apportionment compared to a conventional analysis using the entire data. Festival-related sources (e.g., fireworks and residential burning here) have been clearly identified and estimated during both the Spring and Lantern Festivals. During this period, the sources changed because the time period overlaps with the outbreak of COVID-19 and related reductions in activity during the lockdown that began on Lunar New Year. Multiple PMF runs providing source contribution estimates made it possible to estimate the uncertainties in these values. Our results show that winds-dependent sources like dust and distant point sources have larger uncertainties than the other sources. Compared with conventional PMF analyses, the current method may better reflect the actual emissions as well as being able to estimate uncertainties. Thus, this approach appears to be an improvement if the appropriate data are available.

The Mugan Plain is the most productive area in the Republic of Azerbaijan, but a previous study confirmed trace metal and metalloid (TM&M) contamination with Cr, Ni and Pb, and the potential ecological risk of As was estimated. However, no industrial activity was previously reported in this area; thus, a source apportionment model using positive matrix factorization (PMF) was employed to identify pollution sources, and a human health risk assessment was conducted to evaluate noncarcinogenic and carcinogenic risks. Surface soil samples were collected from 349 sites, and six major elements (Si, Ca, Cl, P, S and Sr) and 8 TM&Ms (As, Cd, Cr, Co, Cu, Ni, Pb and Zn) were analyzed by X-ray fluorescence and employed for further apportionment and risk assessment. As a result, the PMF model showed 7 factors, assigned to natural activity (12.9%), dry riverbed (13.6%), surface accumulation (3.1%), desalinization activity (3.2%), residential activity (12.3%), fossil fuel combustion (35.5%) and agricultural activity (19.3%). The PMF model characterized certain areas with desalinization activity in the previous Soviet period and with surface accumulation of salt, and these findings were confirmed by additional field surveys and historical Landsat satellite images. The risk assessment results showed that there was no risk for the adults, while for children, there was a noncarcinogenic risk, but no carcinogenic risk. Dermal contact was estimated to be the primary pathway, and Ni and As were identified as the most problematic TM&Ms for noncarcinogenic and carcinogenic risks, respectively. According to the results, fossil fuel combustion associated with heating and vehicle transportation was estimated to be the main source of pollution, contributing 42.6% of the noncarcinogenic and 48.0% of the carcinogenic risks. These results can provide scientific guidance to understand and prevent the risk of TM&Ms on the Mugan Plain.

Organic and inorganic pollutants are often co-sedimentary in soils and have the same sources in the urban environment. The identification of the sources and distribution of combined pollutants is a basic step in risk management. In this study, the levels of polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) were measured in urban park soils in Beijing. Bivariate local Moran’s I and positive matrix factorization (PMF) source apportionment were used to identify the spatial clustering patterns and potential sources of PAHs and HMs, as well as to ultimately define a pollution risk control area. The results revealed an obvious clustered distribution of PAHs and HMs in the park soils. High-high areas were defined as sites containing a complex mixture of pollutants, which were mainly located in the center and north of Beijing. High-low and low-high areas were located outside the city center but had the potential for combined pollution, and therefore require continuous attention. Bivariate local indicators of spatial association (LISA) enabled a more accurate analyses of the mechanism controlling the spatial distribution of PAH and HM combinations in urban parks. The source apportionment indicated that industrial and traffic emissions were the most important sources of the pollutant combinations in urban parks, with traffic emissions accounting for most of the pollution.

Exposure to household air pollution (HAP) from solid fuel use (SFU) causes millions of premature deaths globally. Direct leakage from stoves into indoor air is believed to be the main cause of severe HAP. However, previous laboratory-based measurements reported leakage of minimal fractions from wood fuel combustion. Using a newly developed measurement method, on-site measurements were conducted to quantitatively evaluate the leakage of gases and particulate matter from different fuel-stove combinations. The fraction of indoor leakage to the total emission (F) of the measured air pollutants varied from 23 ± 11% to 40 ± 16% for different pollutants and fuel-stove combinations, and these were significantly higher than previously lab-based results. Fuel differences overwhelmed stove differences in influencing F values, with higher values from biomass burning than from coal combustion. The particles had higher F values than gases. Fugitive emission rates (ERs) were log-normally distributed, and biomass burning had higher ERs than coal burning. Indoor PM₂.₅ (fine particulate matter) and CO (carbon monoxide) concentrations measured during the burning period increased by nearly 1–2 orders of magnitude compared to concentrations before or after burning, confirming substantially high indoor leakage from fuel combustion in cookstoves. High fugitive emissions in indoor cookstoves quantified from the present on-site measurements effectively explain the high HAP levels observed in rural SFU households, and call for interventions to improve indoor air quality.

Arsenic contamination of ground water is a worldwide issue, causing a number of ailments in humans. As an engineered and integrated solution, a hybrid vertical subsurface flow constructed wetland (VSSF-CW) amended with BCXZM composite (Bacillus XZM immobilized on rice husk biochar), was found effective for the bioremediation of arsenic contaminated water. Biological filter was prepared by amending top 3 cm of VSSF-CW bed with BCXZM. This filter scavenged ∼64% of total arsenic and removal efficiency of ∼95% was achieved by amended and planted (As + P + B) VSSF-CW, while non-amended (As + P) VSSF-CW showed a removal efficiency of ∼55%. The unplanted and amended (As + B) VSSF-CW showed a removal efficiency of ∼70%. The symbiotic association of Bacillus XZM, confirmed by SEM micrographs, significantly (p ≤ 0.05) reduced reactive oxygen species (ROS) and malondialdehyde (MDA) accumulation in Typha latifolia, hence, increasing the plant growth (2 folds). An increase in the indole acetic acid (IAA) and arsenic accumulation in plant was also observed in As + P + B system. The removal efficiency of the system was compromised after 4th consecutive cycle and 48 h was observed as optimum retention time. The FTIR-spectra showed the involvement of -N-H bond, carboxylic acids, –CH₂ stretching of –CH₂ and –CH₃, carbonyl groups, -C-H, C–O–P and C–O–C, sulphur/thiol and phosphate functional groups in the bio-sorption of arsenic by BCXZM filter. Our study is a first reported on the simultaneous phytoextraction and biosorption of arsenic in a hybrid VSSF-CW. It is proposed that BCXZM can be applied effectively in CWs for the bioremediation of arsenic contaminated water on large scale.

The infrastructures of coal-fired power plants in China have changed significantly since 2010, but the magnitude and characteristics of polycyclic aromatic hydrocarbon (PAH) emissions remain to be updated. In the present study, a unit-based PAH emission inventory for coal-fired power plants between 2010 and 2017 was constructed for Anhui Province, China. Atmospheric PAH emissions from pulverized coal (PC) and circulating fluidized bed (CFB) units in 2017 were 8600 kg and 7800 kg, respectively. The emission rates and intensities for CFB units (7.2 kg ton⁻¹ and 2.1 kg MW⁻¹) were significantly higher than those for PC units (1.1 kg ton⁻¹ and 0.19 kg MW⁻¹), primarily because CFB boilers were operated at lower combustion temperatures and poor combustion conditions compared to PC boilers. The distribution patterns of PAH emissions across different age groups largely reflected the time periods for constructing coal-fired units in Anhui and for the transition of small units to large ones. The accomplishment of ultralow emission technologies and phase-out of outdated coal-fired units were responsible for the decreasing trend of PAH emissions between 2012 and 2017. The warmer summer in 2013 and 2017 and colder winter in 2011 compared to other years probably caused increased use of air conditioners, resulting in increased electricity consumption and PAH emissions. Future PAH emissions would decrease by 45–57% during 2017–2030, benefitting from power plant fleet optimization, i.e., phasing out outdated coal-fired units and replacing them with large ones. With the best available optimized power plant fleets and end-of-pipe control measures accomplished in Anhui’s CFPPs, PAH emissions in 2030 would potentially be reduced by 56–65%.