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Ji K.,Key Laboratory of Beijing on Regional Air Pollution Control | Ji K.,Beijing University of Chemical Technology | Ji K.,Tohoku University | Dai H.,Key Laboratory of Beijing on Regional Air Pollution Control | And 9 more authors.
Applied Catalysis B: Environmental | Year: 2015

Three-dimensionally ordered macroporous (3DOM) photocatalysts BiVO4 (denoted as 3D-BiV), AgBr/3D-BiV, and 0.17wt% M/AgBr/3D-BiV (MAu, Pt, and Pd) were prepared using the polymethyl methacrylate-templating, low-temperature deposition, and polyvinyl alcohol-protected reduction methods, respectively. The as-prepared BiVO4 possessed a good-quality 3DOM structure and a high surface area. It is found that the AgBr and noble metals were uniformly distributed on the surface of 3D-BiV. Among the M/AgBr/3D-BiV samples, the 0.17wt% Pd/AgBr/3D-BiV sample showed the highest photocatalytic activity for the degradation of 4-chlorophenol (4-CP) under visible light illumination (i.e., complete 4-CP degradation could be achieved within 150min), which was associated with its good 3DOM structure, high surface oxygen adspecies concentration, easy transfer and separation of photogenerated carriers, and synergistic effect between AgBr or Pd nanoclusters and BiVO4. © 2014 Elsevier B.V.

Wei W.,Beijing University of Technology | Wei W.,Key Laboratory of Beijing on Regional Air Pollution Control | lv Z.,Beijing University of Technology | lv Z.,Key Laboratory of Beijing on Regional Air Pollution Control | And 9 more authors.
Environmental Monitoring and Assessment | Year: 2015

This study selected a petrochemical industrial complex in Beijing, China, to understand the characteristics of surface ozone (O3) in this industrial area through the on-site measurement campaign during the July–August of 2010 and 2011, and to reveal the response of local O3 to its precursors’ emissions through the NCAR-Master Mechanism model (NCAR-MM) simulation. Measurement results showed that the O3 concentration in this industrial area was significantly higher, with the mean daily average of 124.6 μg/m3 and mean daily maximum of 236.8 μg/m3, which are, respectively, 90.9 and 50.6 % higher than those in Beijing urban area. Moreover, the diurnal O3 peak generally started up early in 11:00–12:00 and usually remained for 5–6 h, greatly different with the normal diurnal pattern of urban O3. Then, we used NCAR-MM to simulate the average diurnal variation of photochemical O3 in sunny days of August 2010 in both industrial and urban areas. A good agreement in O3 diurnal variation pattern and in O3 relative level was obtained for both areas. For example of O3 daily maximum, the calculated value in the industrial area was about 51 % higher than in the urban area, while measured value in the industrial area was approximately 60 % higher than in the urban area. Finally, the sensitivity analysis of photochemical O3 to its precursors was conducted based on a set of VOCs/NOx emissions cases. Simulation results implied that in the industrial area, the response of O3 to VOCs was negative and to NOx was positive under the current conditions, with the sensitivity coefficients of −0.16~−0.43 and +0.04~+0.06, respectively. By contrast, the urban area was within the VOCs-limitation regime, where ozone enhancement in response to increasing VOCs emissions and to decreasing NOx emission. So, we think that the VOCs emissions control for this petrochemical industrial complex will increase the potential risk of local ozone pollution aggravation, but will be helpful to inhibit the ozone formation in Beijing urban area through reducing the VOCs transport from the industrial area to the urban area. © 2015, Springer International Publishing Switzerland.

Wei W.,Beijing University of Technology | Wei W.,Key Laboratory of Beijing on Regional Air Pollution Control | Lv Z.,Beijing University of Technology | Yang G.,Beijing University of Technology | And 4 more authors.
Environmental Pollution | Year: 2016

This study aimed to apply an inverse-dispersion calculation method (IDM) to estimate the emission rate of volatile organic compounds (VOCs) for the complicated industrial area sources, through a case study on a petroleum refinery in Northern China. The IDM was composed of on-site monitoring of ambient VOCs concentrations and meteorological parameters around the source, calculation of the relationship coefficient γ between the source's emission rate and the ambient VOCs concentration by the ISC3 model, and estimation of the actual VOCs emission rate from the source. Targeting the studied refinery, 10 tests and 8 tests were respectively conducted in March and in June of 2014. The monitoring showed large differences in VOCs concentrations between background and downwind receptors, reaching 59.7 ppbv in March and 248.6 ppbv in June, on average. The VOCs increases at receptors mainly consisted of ethane (3.1%–22.6%), propane (3.8%–11.3%), isobutane (8.5%–10.2%), n-butane (9.9%–13.2%), isopentane (6.1%–12.9%), n-pentane (5.1%–9.7%), propylene (6.1–11.1%) and 1-butylene (1.6%–5.4%). The chemical composition of the VOCs increases in this field monitoring was similar to that of VOCs emissions from China's refineries reported, which revealed that the ambient VOCs increases were predominantly contributed by this refinery. So, we used the ISC3 model to create the relationship coefficient γ for each receptor of each test. In result, the monthly VOCs emissions from this refinery were calculated to be 183.5 ± 89.0 ton in March and 538.3 ± 281.0 ton in June. The estimate in June was greatly higher than in March, chiefly because the higher environmental temperature in summer produced more VOCs emissions from evaporation and fugitive process of the refinery. Finally, the VOCs emission factors (g VOCs/kg crude oil refined) of 0.73 ± 0.34 (in March) and 2.15 ± 1.12 (in June) were deduced for this refinery, being in the same order with previous direct-measurement results (1.08–2.65 g VOCs/kg crude oil refined). An inverse-dispersion calculation method was applied to estimate VOCs emission rate for a petroleum refinery, being 183.5 ton/month (March) and 538.3 ton/month (June). © 2016 Elsevier Ltd

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