Abstract. Trees can significantly impact the urban air chemistry by the uptake and emission of reactive biogenic volatile organic compounds (BVOCs), which are involved in ozone and particle formation. Here we present the emission potentials of "constitutive" (cBVOCs) and "stress-induced" BVOCs (sBVOCs) from the dominant broadleaf woody plant species in the megacity of Beijing. Based on the municipal tree census and cuvette BVOC measurements on leaf level, we built an inventory of BVOC emissions, and assessed the potential impact of BVOCs on secondary organic aerosol (SOA) formation in 2005 and 2010, i.e., before and after realizing the large tree-planting program for the 2008 Olympic Games. We found that sBVOCs, such as fatty acid derivatives, benzenoids, and sesquiterpenes, constituted a significant fraction ( ∼ 40 %) of the total annual BVOC emissions, and we estimated that the overall annual BVOC budget may have doubled from ∼ 4.8 × 10 9 g C year −1 in 2005 to ∼ 10.3 × 10 9 g C year −1 in 2010 due to the increase in urban greening, while at the same time the emission of anthropogenic VOCs (AVOCs) decreased by 24 %. Based on the BVOC emission assessment, we estimated the biological impact on SOA mass formation potential in Beijing. Constitutive and stress-induced BVOCs might produce similar amounts of secondary aerosol in Beijing. However, the main contributors of SOA-mass formations originated from anthropogenic sources (> 90 %). This study demonstrates the general importance to include sBVOCs when studying BVOC emissions. Although the main problems regarding air quality in Beijing still originate from anthropogenic activities, the present survey suggests that in urban plantation programs, the selection of low-emitting plant species has some potential beneficial effects on urban air quality.

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The most widely used high power industrial lasers are the Nd:YAG and CO2 lasers. The chemical oxygen iodine laser (COIL), whose wavelength (1.315 μm) is between that of the Nd:YAG (1.06 μm) and CO2 (10.6 μm) lasers, is another high power laser for industrial applications. The cutting capability of these lasers is investigated in this paper. The cut depth strongly depends on the absorptivity of the cut material, kerf width and cutting speed. The absorptivity is an unknown parameter for which experimental data at high temperatures are currently unavailable. Theoretical values of the absorptivities of various metals are obtained using the Hagen-Ruben relationship. It is found that the absorptivity of a metal is linearly proportional to the square root of its resistivity and also inversely proportional to the square root of the wavelength. The absorptivities of the COIL and Nd:YAG lasers are 2.84 and 3.16 times larger than that of the CO2 laser, respectively. Based on these theoretical values of the absorptivity, the cut depths for several metals are analyzed at various laser powers and cutting speeds for these lasers. For identical cutting parameters, the cut depths for stainless steel and titanium are deeper than those of most other metals. Due to the wavelength dependence of the absorptivity, the cut depths for COIL and Nd:YAG lasers are expected to be 2.84 and 3.16 times deeper than that for the CO2 laser.

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In many unmanned aerial vehicle (UAV) applications such as land assessment, search and rescue, and precision agriculture, UAVs are often required to survey multiple spatially distributed regions. To perform these applications, one of the key steps is to plan the path for the UAV to quickly cover all regions. The new path planning problem explored here, which we call the TSP-CPP problem, can be viewed as an integration of the traveling salesman problem (TSP) and the coverage path planning (CPP) problem, which has not been well studied in the literature. In this paper, we conduct a systematic investigation on the TSP-CPP problem. In particular, we first provide a mixed integer programming formulation for this new problem, and then introduce a CPP method for covering a single convex polygonal region. Based on this method, we then develop two approaches to solve the TSP-CPP problem, including 1) a dynamic programming-based exact approach that can find the (near) optimal tour, and 2) a heuristic approach that can generate high-quality tours very efficiently. Through comprehensive theoretical analyses and simulation studies, we demonstrate the optimality and efficiency of the proposed approaches. INDEX TERMS Path planning, traveling salesman problem, coverage path planning, multiple convex polygonal regions, unmanned aerial vehicle, optimal path, heuristic algorithm.

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