ABSTRACT
In this research, a novel vehicle-borne system of measuring three-dimensional (3-D) urban data using single-row laser range scanners is proposed. Two single-row laser range scanners are mounted on the roof of a vehicle, doing horizontal and vertical profiling respectively. As the vehicle moves ahead, a horizontal and a vertical range profile of the surroundings are captured at each odometer trigger. The freedom of vehicle motion is reduced from six to three by assuming that the ground surface is flat and smooth so resulting in the vehicle moving on almost the same horizontal plane. Horizontal range profiles, which have an overwhelming overlay between successive ones, are registered to trace vehicle location and attitude. Vertical range profiles are aligned to the coordinate system of the horizontal one according to the physical geometry between the pair of laser range scanners, and subsequently to a global coordinate system to make up 3-D data. An experiment is conducted where 3-D data of a real urban scene is obtained by registering and integrating 2412 horizontal and vertical range profiles. Two ground truths are used in examination. They are the outputs of a GPS/INS/Odometer based positioning system and a 1:500 digital map of the testing site. Accuracy and efficiency of the method in measuring 3-D urban scene is demonstrated.
ABSTRACT
Water quality associated with nitrate (NO3-) leaching from agricultural soils is an important environmental issue. This paper describes a new modelling approach to quantitatively evaluate the effect of the use of fertilisers on global nitrate leaching. A global process-based simulation model was previously developed for the nitrogen cycle in terrestrial ecosystems, in which soil inorganic nitrogen in the form of ammonium (NH4+) and NO3- was considered. After introducing data on world fertiliser consumption (FAO, 1995) into the steady-state model, the extent of disturbance to the nitrogen cycle caused by fertilisation was calculated. Although fertilisation resulted in an annual increase in net primary production (NPP, represented as carbon) of 18 Gt year-1, NO3- leaching and gaseous losses of nitrogen oxides and ammonia were also accelerated. Most regions with heavy fertiliser application (over 100 kg ha-1 year-1) showed a high annual leaching load equal to or more than 20 kg ha-1 year-1. About 2.5% of the land area occupied by terrestrial ecosystems suffered a serious leaching load of more than 30 kg ha-1 year-1. Of the total amount of applied fertilisers (138 Tg year-1) 19% was lost to NO3- leaching, 8% to gaseous ammonia, and 3% to gaseous nitrogen oxides. The rest was assumed to be fixed in the ecosystems through vegetation uptake.
Subject(s)
Environmental Monitoring/methods , Environmental Pollution/prevention & control , Feces , Fertilizers , Models, Biological , Models, Chemical , Nitrates , Ammonia , Animals , Ecosystem , Humans , NitrogenABSTRACT
The ammonia-oxidizing chemoautotrophic Nitrosomonas sp. strain K1 exhibited marked ribulose-1,5-bisphosphate carboxylase (RubisCO) activity. The RubisCO [EC 4.1.1.39] was purified as an electrophoretically homogeneous protein. The molecular mass of the enzyme was estimated to be about 460 kDa by gel filtration, and it consists of two subunits [large (L): 52.2 kDa; small (S): 13.3 kDa] as demonstrated by SDS-PAGE. This confirmed that the enzyme has an L(8)S(8) structure. The K(m) values of the enzyme for RuBP, NaHCO3, and Mg2+ were estimated to be 0.112, 0.415, and 1.063 mM, respectively. The optimum pH and temperature for its activity were approximately 7.0 and 45 degrees C. The enzyme was stable up to 45 degrees C and in a pH range from 7.0-9.0 (4 degrees C, 48 h). The enzyme activity was inhibited by Cu2+, Hg2+, N-ethylmaleimide, p-chloromercuribenzoate, and SDS (0.1 mM). The activity was also inhibited by ammonium sulfate at high concentrations (38-303 mM) but the stability of the enzyme showed no inhibition at the same ammonium sulfate concentrations. The N-terminal amino acid sequences of the large and small subunits are AIKTYQAGVKEYRQTYW QPDYVPL and AIQAYHLTKKYETFSYLPQM, respectively.
