We report data on the martian meteorite Northwest Africa (NWA) 7034, which shares some petrologic and geochemical characteristics with known martian meteorites of the SNC (i.e., shergottite, nakhlite, and chassignite) group, but also has some unique characteristics that would exclude it from that group. NWA 7034 is a geochemically enriched crustal rock compositionally similar to basalts and average martian crust measured by recent Rover and Orbiter missions. It formed 2.089 ± 0.081 billion years ago, during the early Amazonian epoch in Mars' geologic history. NWA 7034 has an order of magnitude more indigenous water than most SNC meteorites, with up to 6000 parts per million extraterrestrial H(2)O released during stepped heating. It also has bulk oxygen isotope values of Δ(17)O = 0.58 ± 0.05 per mil and a heat-released water oxygen isotope average value of Δ(17)O = 0.330 ± 0.011 per mil, suggesting the existence of multiple oxygen reservoirs on Mars.

Abstract. Daily PM2.5 (aerosol particles with an aerodynamic diameter of less than 2.5 μm) samples were collected at an urban site in Chengdu, an inland megacity in southwest China, during four 1-month periods in 2011, with each period in a different season. Samples were subject to chemical analysis for various chemical components ranging from major water-soluble ions, organic carbon (OC), element carbon (EC), trace elements to biomass burning tracers, anhydrosugar levoglucosan (LG), and mannosan (MN). Two models, the ISORROPIA II thermodynamic equilibrium model and the positive matrix factorization (PMF) model, were applied to explore the likely chemical forms of ionic constituents and to apportion sources for PM2.5. Distinctive seasonal patterns of PM2.5 and associated main chemical components were identified and could be explained by varying emission sources and meteorological conditions. PM2.5 showed a typical seasonality of waxing in winter and waning in summer, with an annual mean of 119 μg m−3. Mineral soil concentrations increased in spring, whereas biomass burning species elevated in autumn and winter. Six major source factors were identified to have contributed to PM2.5 using the PMF model. These were secondary inorganic aerosols, coal combustion, biomass burning, iron and steel manufacturing, Mo-related industries, and soil dust, and they contributed 37 ± 18, 20 ± 12, 11 ± 10, 11 ± 9, 11 ± 9, and 10 ± 12%, respectively, to PM2.5 masses on annual average, while exhibiting large seasonal variability. On annual average, the unknown emission sources that were not identified by the PMF model contributed 1 ± 11% to the measured PM2.5 mass. Various chemical tracers were used for validating PMF performance. Antimony (Sb) was suggested to be a suitable tracer of coal combustion in Chengdu. Results of LG and MN helped constrain the biomass burning sources, with wood burning dominating in winter and agricultural waste burning dominating in autumn. Excessive Fe (Ex-Fe), defined as the excessive portion in measured Fe that cannot be sustained by mineral dust, is corroborated to be a straightforward useful tracer of iron and steel manufacturing pollution. In Chengdu, Mo / Ni mass ratios were persistently higher than unity, and considerably distinct from those usually observed in ambient airs. V / Ni ratios averaged only 0.7. Results revealed that heavy oil fuel combustion should not be a vital anthropogenic source, and additional anthropogenic sources for Mo are yet to be identified. Overall, the emission sources identified in Chengdu could be dominated by local sources located in the vicinity of Sichuan, a result different from those found in Beijing and Shanghai, wherein cross-boundary transport is significant in contributing pronounced PM2.5. These results provided implications for PM2.5 control strategies.

Abstract. Daily PM2.5 (aerosol particles with an aerodynamic diameter of less than 2.5 μm) samples were collected at an urban site in Chengdu, an inland megacity in southwest China, during four one-month periods in 2011, with each period in a different season. Samples were subjected to chemical analysis for various chemical components ranging from major water-soluble ions, organic carbon (OC), element carbon (EC), trace elements to biomass burning tracers, anhydrosugar levoglucosan (LG) and mannosan (MN). Two models, ISORROPIA-II thermodynamic equilibrium model and positive matrix factorization (PMF) model, were applied to explore the likely chemical forms of ionic constituents and to apportion sources for PM2.5. Distinctive seasonal patterns of PM2.5 and associated main chemical components were identified and could be explained by varying emission sources and meteorological conditions. PM2.5 showed a typical seasonality of waxing in winter and waning in summer, with an annual mean of 119 μg m−3. Mineral soil concentrations increased in spring whereas biomass burning species elevated in autumn and winter. Six major source factors were identified to have contributed to PM2.5 using the PMF model. These were secondary inorganic aerosols, coal combustion, biomass burning, iron and steel manufacturing, Mo-related industries, and soil dust, and they contributed 37 ± 18%, 20 ± 12%, 11 ± 10%, 11 ± 9%, 11 ± 9%, and 10 ± 12%, respectively, to PM2.5 masses on annual average, while exhibiting large seasonal variability. On annual average, the unknown emission sources that were not identified by the PMF model contributed 1 ± 11% to the measured PM2.5 mass. Various chemical tracers were used for validating PMF performance. Antimony (Sb) was suggested to be a suitable tracer of coal combustion in Chengdu. Results of LG and MN helped constrain the biomass burning sources, with wood burning dominating in winter and agricultural waste burning dominating in autumn. Excessive Fe (Ex-Fe), defined as excessive portion in measured Fe that cannot be sustained by mineral dust, is corroborated to be a straightforward useful tracer of iron and steel manufacturing pollution. In Chengdu, Mo/Ni mass ratios were persistently higher than unity, and considerably distinct from those usually observed in ambient airs. V/Ni ratios averaged at only 0.7. Results revealed that heavy oil fuel combustion should not be a vital anthropogenic source, and additional anthropogenic sources for Mo are yet to be identified. Overall, the emission sources identified in Chengdu could be dominated by local sources located in the vicinity of Sichuan, a result differed from those found in Beijing and Shanghai, wherein cross-boundary transport is significant in contributing pronounced PM2.5. These results provided implications for PM2.5 control strategies.

Abstract. Particulate matter (PM) pollution in China is an emerging environmental issue which policy makers and the public have increasingly paid attention to. In order to investigate the characteristics, sources, and chemical processes of PM pollution in Guangzhou, field measurements were conducted from 20 November 2017 to 5 January 2018, with a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) and other collocated instruments. Mass concentrations of non-refractory submicron particulate matter (NR-PM1) measured by the ToF-ACSM correlated well with those of PM2.5 or PM1.1 measured by filter-based methods. The organic mass fraction increased from 45 % to 53 % when the air switched from non-pollution periods to pollution episodes (EPs), indicating significant roles of organic aerosols (OAs) during the whole study. Based on the mass spectra measured by the ToF-ACSM, positive matrix factorization (PMF) with the multilinear engine (ME-2) algorithm was performed to deconvolve OA into four factors, including hydrocarbon-like OA (HOA, 12 %), cooking OA (COA, 18 %), semi-volatile oxygenated OA (SVOOA, 30 %), and low-volatility oxygenated OA (LVOOA, 40 %). Furthermore, we found that SVOOA and nitrate were significantly contributed from local traffic emissions while sulfate and LVOOA were mostly attributed to regional pollutants. Comparisons between this work and other previous studies in China show that secondary organic aerosol (SOA) fraction in total OA increases spatially across China from the north to the south. Two distinctly opposite trends for NR-PM1 formation were observed during non-pollution periods and pollution EPs. The ratio of secondary PM (SPM = SVOOA + LVOOA + sulfate + nitrate + ammonium) to primary PM (PPM = HOA + COA + chloride), together with peroxy radicals RO2∗ and ozone, increased with increasing NR-PM1 concentration during non-pollution periods, while an opposite trend of these three quantities was observed during pollution EPs. Furthermore, oxidation degrees of both OA and SOA were investigated using the f44∕f43 space and the results show that at least two OOA factors are needed to cover a large range of f44 and f43 in Guangzhou. Comparisons between our results and other laboratory studies imply that volatile organic compounds (VOCs) from traffic emissions, in particular from diesel combustion and aromatic compounds, are the most likely SOA precursors in Guangzhou. Peroxy radical RO2∗ was used as a tracer for SOA formed through gas-phase oxidation. For non-pollution periods, SOA concentration was reasonably correlated with RO2∗ concentration during both daytime and nighttime, suggesting that gas-phase oxidation was primarily responsible for SOA formation. However, there was no correlation between SOA and RO2∗ in pollution EPs, suggesting a dramatically changed mechanism for SOA formation. This conclusion can also be supported by different features of SOA in a van Krevelen diagram between non-pollution periods and pollution EPs. Furthermore, for pollution EPs, when NR-PM1 mass concentration was divided into six segments, in each segment except for the lowest one SOA concentration was correlated moderately with RO2∗ concentration, suggesting that gas-phase oxidation still plays important roles in SOA formation. The intercepts of the above linear regressions, which likely correspond to the extent of other mechanisms (i.e., heterogeneous and multiphase reactions), increase with increasing NR-PM1 mass concentration. Our results suggest that while gas-phase oxidation contributes predominantly to SOA formation during non-pollution periods, other mechanisms such as heterogeneous and multiphase reactions play more important roles in SOA formation during pollution EPs than gas-phase oxidation.

Long non-coding RNAs (lncRNAs) have proved to act as crucial biomarkers in tumors. Novel biomarkers in non-small cell lung cancer (NSCLC) need to be investigated badly. To identify the differentially expressed lncRNAs between NSCLC tissue and adjacent tissue, microarray analysis was performed. lncRNA SLC16A1-AS1 was significantly less expressed in NSCLC tissue than that in adjacent tissue. Gain-of-function experiments was performed to determine the biological functions of SLC16A1-AS. In situhybridization and survival analysis were applied in lung cancer tissue samples to determine the prognostic role of SLC16A1-AS1. It was showed that SLC16A1-AS1 was remarkably downregulated in NSCLC tissues and cell lines. Functionally, SLC16A1-AS1 overexpression could inhibit the viability and proliferation of lung cancer cell, block the cell cycle and promote cell apoptosis in vitro which may result from reduced phosphorylation of rat sarcoma (RAS)/ proto-oncogene serine/threonine-protein kinase (RAF)/ mitogen-activated protein kinase kinase (MEK)/ extracellular regulated protein kinases (ERK) pathway caused by elevated expression of SLC16A1-AS1. Clinical sample analysis showed that SLC16A1-AS1 had a favorable impact on the overall survival and progression-free survival of patients with NSCLC. Our results suggested that SLC16A1-AS1 may act as a potential biomarker for patients with NSCLC.

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Twenty trace elements in fine particulate matters (i.e., PM2.5) at urban Chengdu, a southwest megacity of China, were determined to study the characteristics, sources and human health risk of particulate toxic heavy metals. This work mainly focused on eight toxic heavy metal elements (As, Cd, Cr, Cu, Mn, Ni, Pb and Zn). The average concentration of PM2.5 was 165.1 ± 84.7 µg m(-3) during the study period, significantly exceeding the National Ambient Air Quality Standard (35 µg m(-3) in annual average). The particulate heavy metal pollution was very serious in which Cd and As concentrations in PM2.5 significantly surpassed the WHO standard. The enrichment factor values of heavy metals were typically higher than 10, suggesting that they were mainly influenced by anthropogenic sources. More specifically, the Cr, Mn and Ni were slightly enriched, Cu was highly enriched, while As, Cd, Pb and Zn were severely enriched. The results of correlation analysis showed that Cd may come from metallurgy and mechanical manufacturing emissions, and the other metals were predominately influenced by traffic emissions and coal combustion. The results of health risk assessment indicated that As, Mn and Cd would pose a significant non-carcinogenic health risk to both children and adults, while Cr would cause carcinogenic risk. Other toxic heavy metals were within a safe level.

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