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Urban forests have been shown to be efficient for reducing air pollutants especially for particulate matters (PMs). This study aims to reveal the PM blocking capacity of two common artificial landscape species, Sabina chinensis and Liriodendron chinense and to investigate spatial-temporal heterogeneities by estimating the vegetation collection velocity of coarse (PM10) and fine particles (PM2.5) during different seasons and heights. PM concentration and meteorological data were collected on both leeward and windward sides of trees during the daytime in both summers and winters from 2013 to 2015. Concentration and meteorological monitors were installed at three heights, bottom (1.5 m), middle (3.5 m), and top (5.5 m) of the canopy. The results showed: During daytime, the collection velocity changed and PM2.5 collection velocity was much higher than that of PM10. Furthermore, the maximum collection velocities of L. chinense and S. chinensis occurred at 14:00-16:00 both in summer and winter. Moreover, the collection velocity had a positive correlation with wind speed and temperature. The blocking capacities of L. chinense and S. chinensis varied from season to season, and the concentrations of particulate matter indicate the middle canopy of both species as the most effective part for TSP blocking. Furthermore, these two species are more effective blocking in PM2.5 than PM10. The blocking capacity of S. chinensis is generally better. The vegetation collection is the major process of PM removal near the ground and sedimentation was not taken into consideration near the ground.

Atmospheric particulate matter (PM) deposition which involves both dry and wet processes is an important means of controlling air pollution. To investigate the characteristics of dry and wet deposition in wetlands, PM concentrations and meteorological conditions were monitored during summer at heights of 1.5 m, 6 m and 10 m above ground level at Cuihu Wetland (Beijing, China) in order to assess the efficiency of PM2.5 (particles with an aerodynamic size of 6 m (0.007 ± 0.003 μg·m-2·s-1) > 1.5 m (0.005 ± 0.002 μg·m-2·s-1). And the following deposition fluxes for PM10 were recorded: 10 m (2.163 ± 2.941 μg·m-2·s-1) > 1.5 m (1.565 ± 0.872 μg·m-2·s-1) > 6 m (0.987 ± 0.595 μg·m-2·s-1). In the case of wet deposition, the relative deposition fluxes for PM2.5 and PM10 were 1.5 m > 10 m > 6 m, i.e. there was very little difference between the fluxes for PM2.5 (0.688 ± 0.069 μg·m-2·s-1) and for PM10 (0.904 ± 0.103 μg·m-2·s-1). It was also noted that rainfall intensity and PM diameter influenced wet deposition efficiency. Dry deposition (63%) was more tilted towards removing PM10 than was the case for wet deposition (37%). In terms of PM2.5 removal, wet deposition (92%) was found to be more efficient.

In recent years, the rapid development of industrialization and urbanization has caused serious environmental pollution, especially particulate pollution. As the "Earth's kidneys," wetland plays a significant role in improving the environmental quality and adjusting the climate. To study how wetlands work in this aspect, from the early autumn of 2014 to 2015, we implemented a study to measure the PM concentration and chemical composition at three heights (1.5, 6, and 10 m) during different periods (dry, normal water, and wet periods) in the Cuihu wetland park in Beijing for analyzing the dry deposition flux and the effect of meteorological factors on the concentration. Results indicated that (1) the diurnal variations of the PM2.5 and PM10 concentrations at the three heights were similar in that the highest concentration occurred at night and the lowest occurred at noon, and the daytime concentration was lower than that at night; (2) the PM2.5 and PM10 concentrations also varied between different periods that wet period > normal water period > wet period, and the concentration at different heights during different periods varied. In general, the lowest concentration occurred at 10 m during the dry and normal water periods, and the highest concentration occurred at 1.5 m during the wet period. (3) SO42-, NO3-, and Cl- are the dominant constituents of PM2.5, accounting for 42.22, 12.6, and 21.56%, respectively; (4) the dry depositions of PM2.5 and PM10 at 10 m were higher than those at 6 m, and the deposition during the dry period was higher than those during the wet and normal water periods. In addition, the deposition during the night-time was higher than that during the daytime. Moreover, meteorological factors affected the deposition, the temperature and wind speed being negatively correlated with the deposition flux and the humidity being positively correlated. (5) The PM10 and PM2.5 concentrations were influenced by meteorological factors. The PM2.5 and PM10 concentrations were negatively correlated with temperature and wind speed but positively correlated with relative humidity.

In bulk heterojunction photovoltaic systems both the open-circuit voltage as well as the short-circuit current, and hence the power conversion efficiency, are dependent on the optical bandgap of the electron-donor material. While first-principles methods are computationally intensive, simpler model Hamiltonian approaches typically suffer from one or more flaws: inability to optimize the geometries for their own input; absence of general, transferable parameters; and poor performance for non-planar systems. We introduce a set of new and revised parameters for the adapted Su-Schrieffer-Heeger (aSSH) Hamiltonian, which is capable of optimizing geometries, along with rules for applying them to any [Formula: see text]-conjugated system containing C, N, O, or S, including non-planar systems. The predicted optical bandgaps show excellent agreement to UV-vis spectroscopy data points from literature, with a coefficient of determination [Formula: see text], a mean error of -0.05 eV, and a mean absolute deviation of 0.16 eV. We use the model to gain insights from PEDOT, fused thiophene polymers, poly-isothianaphthene, copolymers, and pentacene as sources of design rules in the search for low bandgap materials. Using the model as an in-silico design tool, a copolymer of benzodithiophenes along with a small-molecule derivative of pentacene are proposed as optimal donor materials for organic photovoltaics.