Atmospheric formaldehyde monitoring in the Greater Houston area in 2002

A laser spectrometer based on difference frequency generation (DFG) was deployed for real-time long-term monitoring of HCHO concentrations at an environmental monitoring site located at Deer Park, Texas, in the Greater Houston area. Three HCHO concentration measurements were made during the periods of July 20-31 (period I), August 2-14 (period II), and August 24-September 25 (period III), 2002. In periods I and II, differences in HCHO concentrations are apparent between day and night measurements, with elevated concentrations during daylight hours. Most of the HCHO peak values are less than 20 ppbV except for two intense peaks on August 02 (approximately 25 ppbV) and August 04 (approximately 30 ppbV). The formaldehyde concentration levels in ambient air at the measurement site are produced mainly by the photochemical oxidation of volatile organic compounds (VOCs) caused by intense sunlight during periods I and II. This observation was made based on a comparison with the ozone concentration, solar radiation, temperature, relative humidity, and wind speed data obtained from the Texas Commission on Environmental Quality (TCEQ). During period III, data collected by a time-integrating wet-chemical technique are compared to the data collected by the spectroscopic instrument.     

Complementary energy methods in the computation of electrostatic fields

It is shown how complementary energy methods can be applied to problems involving the calculation of electrostatic fields. The results obtained using such methods provide error bounded solutions to the system energy, and may be compared with those found through application of the conventional finite element method. To illustrate the technique the classical problem of a cylindrical tank, half filled with a charged liquid, is investigated. Comparisons are made on the basis of computer C.P.U. time, and core storage requirements, for a given degree of accuracy in total system energy. The question of local error in primary field quantities is also examined.     

Hormone changes in relation to the time of fetal death after prostaglandin-induced abortion

The changes in unconjugated estradiol-17beta and estriol, progesterone and chorionic somatomammotropin (HCS) in peripheral plasma have been studied in 18 women at 30-minute intervals following intra-uterine prostaglandin E2 administration for therapeutic termination of second trimester pregnancy. The hormonal changes were related to the time of fetal death detected by the disappearance of fetal heart pulsations. Prostaglandin E2 was given by the intra-amniotic route with urea (5 patients) or with intravenous oxytocin (5 patients), or by the extra-amniotic route with intravenous oxytocin (8 patients). Fetal death occurred rapidly with intra-amniotic PGE2, but usually at a late stage with extra-amniotic PGE2. Three fetuses in the extra-amniotic group died at or just before abortion. A variety of fetal heart changes were noted and the time of fetal death did not appear to influence the time of abortion within each treatment subgroup. Estradiol and estriol showed a sligh but persistent fall over 24 hours prior to induction of abortion. A more rapid fall usually occurred after induction, with a consistent fall around the time of fetal death. Progesterone and HCS usually fell much less before and immediately after fetal death. A marked rise in estradiol sometimes occurred before fetal death, particularly in the intraamniotic PGE2 and urea subgroup. Estriol levels declined more rapidly before than after fetal death, whereas fetal death had less consistent effects on the other hormones. All hormones had usually fallen considerably at the time of abortion, and in some individuals marked fluctuations in hormone levels were seen.     

Effects of three types of free-stall surfaces on preferences and stall usage by dairy cows

One important criterion in choosing appropriate housing systems for dairy cattle is that the freestall provides a comfortable surface for the cow. This paper describes two experiments testing the effects of commonly used lying surfaces on stall preference and stall usage by Holstein cows. In both experiments, 12 cows were housed individually in separate pens. Each pen contained three free stalls with a different surface: deep-bedded sawdust, deep-bedded sand, and a geotextile mattress covered with 2 to 3 cm of sawdust. The animals were restricted to each surface in turn, in a random order for either 2 (Experiment 1) or 3 d (Experiment 2). Both before and after this restriction phase, the animals were allowed access to all three surfaces, and preference was determined, based on lying times. Of the 12 cows used in Experiment 1, 10 preferred sawdust before and nine after the restriction phase. During the restriction phase, average lying times and number of lying events during the restriction phase were significantly lower for the sand-bedded stalls (P < or = 0.05), and standing times were higher on mattresses (P < or = 0.05), compared with sawdust. Although these cows had some experience with all three surfaces during the experiment, they had been housed in sawdust-bedded stalls during their previous lactation. Cows used in Experiment 2 had spent their previous lactation in sand bedded stalls. In this experiment, about half the cows preferred sand and half sawdust, after the restriction phase. During the restriction phase of experiment, lying times and number of lying events were lower, and standing times were higher when the animals were restricted to the mattresses compared to either sand or sawdust (P < or = 0.05). These results indicate that (1) free stall surface can affect both stall preferences and stall usage, and (2) mattresses are less preferred.     

Development and analysis of a 12-year daily 1-km forest fire dataset across North America from NOAA/AVHRR data

Fires in boreal and temperate forests play a significant role in the global carbon cycle. While forest fires in North America (NA) have been surveyed extensively by U.S. and Canadian forest services, most fire records are limited to seasonal statistics without information on temporal evolution and spatial expansion. Such dynamic information is crucial for modeling fire emissions. Using the daily Advanced Very High Resolution Radiometer (AVHRR) data archived from 1989 to 2000, an extensive and consistent fire product was developed across the entire NA forest regions on a daily basis at 1-km resolution. The product was generated following data calibration, geo-referencing, and the application of an active fire detection algorithm and a burned area mapping algorithm. The spatial-temporal variation of forest fire in NA is analyzed in terms of (1) annual and monthly patterns of fire occurrences in different eco-domains, (2) the influence of topographic factors (elevation zones, aspect classes, and slope classes), and (3) major forest types and eco-regions in NA. It was found that 1) among the 12 years analyzed, 1989 and 1995 were the most severe fire years in NA; 2) the majority of burning occurred during June-July and in low elevation zones (< 500 m) with gentle slopes (< 10°), except in the dry eco-domain where more fires occurred in higher elevation zones (> 2000 m); 3) most fires occurred in the polar eco-domain, sub-arctic eco-division, and in the taiga ( boreal forests), forest-tundras and open woodlands eco-provinces in the boreal forests of Canada. The tendency for multiple burns to occur increases with elevation and slope until about 2500 m elevation and 24° slope, and decreases therefore. In comparison with ground observations, the omission and commission errors are on the order of 20%.     

On simultaneous on-line state and parameter estimation in non-linear state-space models

On-line estimation plays an important role in process control and monitoring. Obtaining a theoretical solution to the simultaneous state-parameter estimation problem for non-linear stochastic systems involves solving complex multi-dimensional integrals that are not amenable to analytical solution. While basic sequential Monte-Carlo (SMC) or particle filtering (PF) algorithms for simultaneous estimation exist, it is well recognized that there is a need for making these on-line algorithms non-degenerate, fast and applicable to processes with missing measurements. To overcome the deficiencies in traditional algorithms, this work proposes a Bayesian approach to on-line state and parameter estimation. Its extension to handle missing data in real-time is also provided. The simultaneous estimation is performed by filtering an extended vector of states and parameters using an adaptive sequential-importance-resampling (SIR) filter with a kernel density estimation method. The approach uses an on-line optimization algorithm based on Kullback–Leibler (KL) divergence to allow adaptation of the SIR filter for combined state-parameter estimation. An optimal tuning rule to control the width of the kernel and the variance of the artificial noise added to the parameters is also proposed. The approach is illustrated through numerical examples.     

SPOT VEGETATION for characterizing boreal forest fires

The potential of the recent SPOT VEGETATION (VGT) sensor for characterizing boreal forest fires was investigated. Its capability for hotspot detection and burned area mapping was assessed by analysing a series of VGT, NOAA/AVHRR, and Landsat TM images over a 1541 km²     

A biophysically based and objective satellite seasonality observation method for applications over the Arctic

Despite wide applications of remote-sensing data with high temporal resolution for monitoring phenology, two persistent problems have prevented the realization of their full potential. The first is the subjectivity in defining thresholds for a phenological event (e.g. the start or end of growing season ? SOS or EOS). The second is the use of various arbitrarily selected filtering and smoothing algorithms for constructing vegetation index seasonal profiles in order to reduce the noise caused by residue cloud contamination and aerosol variations. In this study, we addressed both problems by developing a biophysically based and objective satellite seasonality observation method (BLOSSOM) for application over Canada’s Arctic. Application of the BLOSSOM method to three northern Canadian national parks (Ivvavik, Wapusk, and Sirmilik) proved that the method is operational. Using the uncertainties in the vegetation index and its threshold, we estimated the overall mean uncertainties as being ?5.3 to 3.4 days, ?4.2 to 5.2 days, and ?6.2 to 8.4 days, respectively, for SOS, EOS, and growing season length (GSL). Further independent tests against SOS, determined using records of snow cover at nearby climate stations (as ‘truth’), indicate that the mean absolute error is less than 3.6 ± 0.2 days.