Facile One-Step Sonochemical Synthesis and Photocatalytic Properties of Graphene/Ag3PO4 Quantum Dots Composites

Abstract In this study, a novel graphene/Ag3PO4 quantum dot (rGO/Ag3PO4 QD) composite was successfully synthesized via a facile one-step photo-ultrasonic-assisted reduction method for the first time. The composites were analyzed by various techniques. According to the obtained results, Ag3PO4 QDs with a size of 1–4 nm were uniformly dispersed on rGO nanosheets to form rGO/Ag3PO4 QD composites. The photocatalytic activity of rGO/Ag3PO4 QD composites was evaluated by the decomposition of methylene blue (MB). Meanwhile, effects of the surfactant dosage and the amount of rGO on the photocatalytic activity were also investigated. It was found that rGO/Ag3PO4 QDs (WrGO:Wcomposite = 2.3%) composite exhibited better photocatalytic activity and stability with degrading 97.5% of MB within 5 min. The improved photocatalytic activities and stabilities were majorly related to the synergistic effect between Ag3PO4 QDs and rGO with high specific surface area, which gave rise to efficient interfacial transfer of photogenerated electrons and holes on both materials. Moreover, possible formation and photocatalytic mechanisms of rGO/Ag3PO4 QDs were proposed. The obtained rGO/Ag3PO4 QDs photocatalysts would have great potentials in sewage treatment and water splitting

Volatile Organic Compounds in a Petrochemical Region in Arid of NW China: Chemical Reactivity and Source Apportionment

We measured volatile organic compounds (VOCs) during the heating, non-heating, and sandstorm periods in the air of the Dushanzi district in NW China and investigated their concentrations, chemical reactivity, and sources. The observed concentrations of total VOCs (TVOCs) were 22.35 +/- 17.60, 33.20 +/- 34.15, and 17.05 +/- 13.61 ppbv in non-heating, heating, and sandstorm periods, respectively. C-2-C-5 alkanes, C-2-C-3 alkenes, benzene, and toluene were the most abundant species, contributing more than 60% of the TVOCs. Among these VOCs, alkenes such as propene had the highest chemical reactivity, accounting for more than 60% of total hydroxyl radical loss rate (L-OH) and ozone formation potential (OFP). Chemical reactivity was the highest in the heating period. The average reaction rate constant (K-OH-avg) and average maximum incremental reactivity coefficient (MIR-avg) of the total observed VOCs were (8.72 +/- 1.42) x 10(-12) cm(3)/mol.s and 2.42 +/- 0.16 mol/mol, respectively. The results of the source apportionment via the Positive Matrix Factorization (PMF) model showed that coal combustion (43.08%) and industrial processes (38.86%) were the major sources of VOCs in the air of the Dushanzi district. The contribution of coal combustion to VOCs was the highest in the heating period, while that of industrial solvents and oil volatilization was the lowest

Polycyclic Aromatic Hydrocarbons in PM2.5 and PM2.5-10 in Urumqi, China: Temporal Variations, Health Risk, and Sources

PM2.5 and PM2.5-10 samples were simultaneously collected in Urumqi from January to December 2011, and 14 priority polycyclic aromatic hydrocarbons (PAHs) were determined. The mean concentrations of total PAHs in PM2.5 and PM2.5-10 were 20.90844.22 ng m(-3) and 19.65176.5 ng m(-3) respectively, with the highest in winter and the lowest in summer. Above 80% of PAHs were enriched in PM2.5, which showed remarkable seasonal variations compared to coarse particles. High molecular weight (HMW) PAHs were predominant in PM2.5 (46.6185.13%), whereas the proportions of lower molecular weight (LMW) and HMW PAHs in PM2.5-10 showed a decreasing and an increasing trend, respectively, from spring to winter. The estimated concentrations of benzo[a]pyrene equivalent carcinogenic potency (BaPeq) in PM2.5 (10.4984.52 ng m(-3)) were higher than that of in PM2.5-10 (1.1513.33 ng m(-3)) except in summer. The estimated value of inhalation cancer risk in PM2.5 and PM2.5-10 were 1.63 x 10(-4)7.35 x 10(-3) and 9.94 x 10(-5)1.16 x 10(-3), respectively, far exceeding the health-based guideline level of 10(-4). Diagnostic ratios and positive matrix factorization results demonstrated that PAHs in PM2.5 and PM2.5-10 were from similar sources, such as coal combustion, biomass burning, coking, and petroleum combustion, respectively. Coal combustion was the most important source for PAHs both in PM2.5 and PM2.5-10, accounting for 54.20% and 50.29%, respectively

Temporal distribution and source apportionment of PM2.5 chemical composition in Xinjiang, NW-China

Daily fine particulate matter samples were collected in Dushanzi district within four months from September 2015 to August 2016 and represent the four seasons. The samples were determined for major chemical components in PM2.5, including elements, water-soluble ions (WSIs) and the organic/elemental carbon (OC/EC). The results indicated that the annual mean PM2.5 concentration was 62.85 +/- 43.5 mu g m(-3) in the Dushanzi district, with the highest seasonal average in winter (95.47 +/- 61.7 mu g m(-3)) and the lowest in summer (33.22 +/- 17.7 mu g m(-3)). The crustal elements were the most abundant elements and accounted for 96.51% of the total analyzed elements. Carcinogenic metals, such as Cr, Pb, As and Cd, originated from human activity, especially during winter. The highest total WSI concentration was 68.99 mu g m(-3) in winter, followed by autumn (16.32 mu g m(-3)), spring (10.23 mu g m(-3)) and summer (7.06 mu g m(-3)). SO42-, NO3- and NH4+ were the most abundant WSIs in Dushanzi. Ion balance calculations showed that PM2.5 in winter was acidic; in autumn and spring alkaline; and in summer nearly neutral. Total carbonaceous aerosol (TCA) accounted for 34% of the PM2.5. The chemical mass closure (CMC) indicated that minerals and WSIs were the major fraction, accounting for 33.58% and 23.17% of PM2.5 mass concentration, respectively. Dushanzi was controlled by four major air masses, and the relative contributions of these air masses differ by season. Positive matrix factorization (PMF) analysis identified six sources including vehicle emission, biomass burning, coal combustion, industrial pollution, secondary aerosols and soil dust, with annual mean contributions of 9.43%, 10.86%, 18.45%, 12.15%, 18.26% and 30.85%, respectively. Moreover, the relative contributions of these identified sources varied significantly with the changing seasons

Simulation of the Ozone Concentration in Three Regions of Xinjiang, China, Using a Genetic Algorithm-Optimized BP Neural Network Model

Accurate ozone concentration simulation can provide a health reference for people’s daily lives. Simulating ozone concentrations is a complex task because near-surface ozone production is determined by a combination of volatile organic compounds (VOCs) and NOx emissions, atmospheric photochemical reactions, and meteorological factors. In this study, we applied a genetic algorithm-optimized back propagation (GA-BP) neural network, multiple linear regression (MLR), BP neural network, random forest (RF) algorithm, and long short-term memory network (LSTM) to model ozone concentrations in three regions of Xinjiang, China (Urumqi, Hotan, and Dushanzi districts) for the first time by inputting wind speed, humidity, visibility, temperature, and wind direction. The results showed that the average relative errors of the model simulations in the Urumqi, Hotan, and Dushanzi districts were BP (61%, 14%, and 16%), MLR (97%, 14%, and 23%), RF (39%, 11%, and 14%), LSTM (50%, 12%, and 16%), and GA-BP (16%, 4%, and 6%) and that the significance coefficients R2 were BP (0.73, 0.65, and 0.83), MLR (0.68, 0.62, and 0.74), RF (0.85, 0.80, and 0.88), LSTM (0.78, 0.74, and 0.85), and GA-BP (0.92, 0.93, and 0.94), respectively, with the simulated values of GA-BP being the closest to the true values. The GA-BP model results showed that among the 100 samples with the same wind speed, humidity, visibility, temperature, and wind direction data, the highest simulated ozone concentrations in the Urumqi, Hotan, and Dushanzi districts were 173.5 μg/m3, 114.3 μg/m3, and 228.4 μg/m3, respectively. The results provide a theoretical basis for the effective control of regional ozone pollution in urban areas (Urumqi), dusty areas (Hotan), and industrial areas (Dushanzi) in Xinjiang

Additional file 1: of Facile One-Step Sonochemical Synthesis and Photocatalytic Properties of Graphene/Ag3PO4 Quantum Dots Composites

Figure S1. TEM images of rGO/Ag3PO4 QDs (stirring method). Figure S2. The plots of (ιhν)2 versus Eg of Ag3PO4 QDs, R-1.5, R-2, R-2.3, R-2.5, and R-3. Figure S3. (a) Photocatalyticdegradation of MB by R-2.3 prepared by different mass of surfactant and (b) apparent rate constants (k) of samples for photocatalytic degradation of MB. Figure S4. (a) Photocatalytic degradation of MB, MO, and RhB byR-2.3, (b) apparent rate constants (k) of sample for photocatalytic degradation of dyes. (ZIP 12230 kb

Temporal Distribution and Source Apportionment of Composition of Ambient PM2.5 in Urumqi, North-West China

In order to identify the pollution characteristics and sources of PM2.5 in Urumqi, fine particulate matter samples were collected from September 2017 to August 2018, and the water-soluble ions (WSIs), organic carbon (OC), elemental carbon (EC), polycyclic aromatic hydrocarbons (PAHs), and metal elements were analyzed. The results indicate that the annual mass concentration of PM2.5 in Urumqi was 158.85 ± 15.11 μg/m3, with the highest seasonal average in autumn (180.49 ± 87.22 μg/m3) and the lowest in summer (148.41 ± 52.60 μg/m3). SO42− (13.58 ± 16.4 μg/m3), NO3− (13.46 ± 17.5 μg/m3), and NH4+ (10.88 ± 12.2 μg/m3) were the most abundant WSIs, and the secondary inorganic ions (SNA = SO42− + NO3− + NH4+) accounted for 87.23% of the WSIs. The NO3−/SO42− ratio indicates that the contribution of stationary sources was dominant. The annual concentrations of OC and EC were 12.00 ± 4.4 µg/m3 and 5.00 ± 3.5 µg/m3, respectively, the OC/EC ratios in winter (2.55 ± 0.7), spring (3.43 ± 1.3), and summer (3.22 ± 1.1) were greater than 2, and there was the formation of secondary organic carbon (SOC). The correlation between OC and EC in spring in Urumqi (R2 = 0.53) was low. In the PM2.5, Al and Fe were the most abundant elements. The highest mass concentration season occurred in autumn, with mass concentrations of 15.11 ± 10.1 µg/m3 and 8.33 ± 6.9 µg/m3, respectively. The enrichment factor (EF) shows that most of the metal elements come from natural sources, and the Cd element mainly comes from anthropogenic sources. PAHs with a middle molecular weight were the main ones, and the annual average annual mass concentration of the PAHs was 451.35 ng/m3. The positive matrix factor model (PMF) source analysis shows that there are five main sources of PM2.5 in Urumqi, including crustal minerals, biomass combustion, coal combustion, vehicular transport, and secondary aerosols. The distribution percentages of these different sources were 19.2%, 10.2%, 12.1%, 8.2%, and 50.3%, respectively