Indoor and outdoor nitrogen dioxide concentration in residential houses in Australia

As part of a larger indoor environmental study, residential indoor and outdoor levels of nitrogen dioxide (NO2) were measured for 14 houses in a suburb of Brisbane, Queensland, Australia. Passive samplers were used for 48-h sampling periods during the winter of 1999. The average indoor and outdoor NO2 levels were 13.8 ± 6.3 and 16.7 ± 4.2 ppb, respectively. The indoor/outdoor NO2 concentration ratio ranged from 0.4 to 2.3, with a median value of 0.82. The results of statistic analyses indicated that there was no significant correlation between indoor and outdoor NO2 concentrations, or between indoor and fixed site NO2 monitoring station concentrations. However, there was a significant correlation between outdoor and fixed site NO2 monitoring station concentrations. There was also a significant correlation between indoor NO2 concentration and indoor submicrometre (0.007–0.808 μm) aerosol particle number concentrations. The results in this study indicated indoor NO2 levels are significantly affected by indoor NO2 sources, such as a gas stove and cigarette smoking. It implies that the outdoor or fixed site monitoring concentration alone is a poor predictor of indoor NO2 concentration.

A Python package for Bayesian estimation using Markov Chain Monte Carlo

Markov chain Monte Carlo (MCMC) estimation provides a solution to the complex integration problems that are faced in the Bayesian analysis of statistical problems. The implementation of MCMC algorithms is, however, code intensive and time consuming. We have developed a Python package, which is called PyMCMC, that aids in the construction of MCMC samplers and helps to substantially reduce the likelihood of coding error, as well as aid in the minimisation of repetitive code. PyMCMC contains classes for Gibbs, Metropolis Hastings, independent Metropolis Hastings, random walk Metropolis Hastings, orientational bias Monte Carlo and slice samplers as well as specific modules for common models such as a module for Bayesian regression analysis. PyMCMC is straightforward to optimise, taking advantage of the Python libraries Numpy and Scipy, as well as being readily extensible with C or Fortran.

Spatial mapping of city-wide PBDE levels using an exponential decay model

Passive air samplers (PAS) consisting of polyurethane foam (PUF) disks were deployed at 6 outdoor air monitoring stations in different land use categories (commercial, industrial, residential and semi-rural) to assess the spatial distribution of polybrominated diphenyl ethers (PBDEs) in the Brisbane airshed. Air monitoring sites covered an area of 1143 km2 and PAS were allowed to accumulate PBDEs in the city's airshed over three consecutive seasons commencing in the winter of 2008. The average sum of five (∑5) PBDEs (BDEs 28, 47, 99, 100 and 209) levels were highest at the commercial and industrial sites (12.7 ± 5.2 ng PUF−1), which were relatively close to the city center and were a factor of 8 times higher than residential and semi-rural sites located in outer Brisbane. To estimate the magnitude of the urban ‘plume’ an empirical exponential decay model was used to fit PAS data vs. distance from the CBD, with the best correlation observed when the particulate bound BDE-209 was not included (∑5-209) (r2 = 0.99), rather than ∑5 (r2 = 0.84). At 95% confidence intervals the model predicts that regardless of site characterization, ∑5-209 concentrations in a PAS sample taken between 4–10 km from the city centre would be half that from a sample taken from the city centre and reach a baseline or plateau (0.6 to 1.3 ng PUF−1), approximately 30 km from the CBD. The observed exponential decay in ∑5-209 levels over distance corresponded with Brisbane's decreasing population density (persons/km2) from the city center. The residual error associated with the model increased significantly when including BDE-209 levels, primarily due to the highest level (11.4 ± 1.8 ng PUF−1) being consistently detected at the industrial site, indicating a potential primary source at this site. Active air samples collected alongside the PAS at the industrial air monitoring site (B) indicated BDE-209 dominated congener composition and was entirely associated with the particulate phase. This study demonstrates that PAS are effective tools for monitoring citywide regional differences however, interpretation of spatial trends for POPs which are predominantly associated with the particulate phase such as BDE-209, may be restricted to identifying ‘hotspots’ rather than broad spatial trends.

Spatial distribution of selected persistent organic pollutants (POPs) in Australia's atmosphere

A nation-wide passive air sampling campaign recorded concentrations of persistent organic pollutants in Australia's atmosphere in 2012. XAD-based passive air samplers were deployed for one year at 15 sampling sites located in remote/background, agricultural and semi-urban and urban areas across the continent. Concentrations of 47 polychlorinated biphenyls ranged from 0.73 to 72 pg m-3 (median of 8.9 pg m-3) and were consistently higher at urban sites. The toxic equivalent concentration for the sum of 12 dioxin-like PCBs was low, ranging from below detection limits to 0.24 fg m-3 (median of 0.0086 fg m-3). Overall, the levels of polychlorinated biphenyls in Australia were among the lowest reported globally to date. Among the organochlorine pesticides, hexachlorobenzene had the highest (median of 41 pg m-3) and most uniform concentration (with a ratio between highest and lowest value [similar]5). Bushfires may be responsible for atmospheric hexachlorobenzene levels in Australia that exceeded Southern Hemispheric baseline levels by a factor of [similar]4. Organochlorine pesticide concentrations generally increased from remote/background and agricultural sites to urban sites, except for high concentrations of [small alpha]-endosulfan and DDTs at specific agricultural sites. Concentrations of heptachlor (0.47-210 pg m-3), dieldrin (ND-160 pg m-3) and trans- and cis-chlordanes (0.83-180 pg m-3, sum of) in Australian air were among the highest reported globally to date, whereas those of DDT and its metabolites (ND-160 pg m-3, sum of), [small alpha]-, [small beta]-, [gamma]- and [small delta]-hexachlorocyclohexane (ND-6.7 pg m-3, sum of) and [small alpha]-endosulfan (ND-27 pg m-3) were among the lowest.

Measuring load of phosphate in the environment by passive sampling techniques: An introduction

Phosphorus has a number of indispensable biochemical roles, but its natural deposition and the low solubility of phosphates as well as their rapid transformation to insoluble forms make the element commonly the growth-limiting nutrient, particularly in aquatic ecosystems. Famously, phosphorus that reaches water bodies is commonly the main cause of eutrophication. This undesirable process can severely affect many aquatic biotas in the world. More management practices are proposed but long-term monitoring of phosphorus level is necessary to ensure that the eutrophication won't occur. Passive sampling techniques, which have been developed over the last decades, could provide several advantages to the conventional sampling methods including simpler sampling devices, more cost-effective sampling campaign, providing flow proportional load as well as representative average of concentrations of phosphorus in the environment. Although some types of passive samplers are commercially available, their uses are still scarcely reported in the literature. In Japan, there is limited application of passive sampling technique to monitor phosphorus even in the field of agricultural environment. This paper aims to introduce the relatively new P-sampling techniques and their potential to use in environmental monitoring studies.

Applications of passive sampling techniques in monitoring organic pollutants in the environment

As there are a myriad of micro organic pollutants that can affect the well-being of human and other organisms in the environment the need for an effective monitoring tool is eminent. Passive sampling techniques, which have been developed over the last decades, could provide several advantages to the conventional sampling methods including simpler sampling devices, more cost-effective sampling campaign, providing time-integrated load as well as representative average of concentrations of pollutants in the environment. Those techniques have been applied to monitor many pollutants caused by agricultural activities, i.e. residues of pesticides, veterinary drugs and so on. Several types of passive samplers are commercially available and their uses are widely accepted. However, not many applications of those techniques have been found in Japan, especially in the field of agricultural environment. This paper aims to introduce the field of passive sampling and then to describe some applications of passive sampling techniques in environmental monitoring studies related to the agriculture industry.

Overfitting Bayesian mixture models with an unknown number of components

This paper proposes solutions to three issues pertaining to the estimation of finite mixture models with an unknown number of components: the non-identifiability induced by overfitting the number of components, the mixing limitations of standard Markov Chain Monte Carlo (MCMC) sampling techniques, and the related label switching problem. An overfitting approach is used to estimate the number of components in a finite mixture model via a Zmix algorithm. Zmix provides a bridge between multidimensional samplers and test based estimation methods, whereby priors are chosen to encourage extra groups to have weights approaching zero. MCMC sampling is made possible by the implementation of prior parallel tempering, an extension of parallel tempering. Zmix can accurately estimate the number of components, posterior parameter estimates and allocation probabilities given a sufficiently large sample size. The results will reflect uncertainty in the final model and will report the range of possible candidate models and their respective estimated probabilities from a single run. Label switching is resolved with a computationally light-weight method, Zswitch, developed for overfitted mixtures by exploiting the intuitiveness of allocation-based relabelling algorithms and the precision of label-invariant loss functions. Four simulation studies are included to illustrate Zmix and Zswitch, as well as three case studies from the literature. All methods are available as part of the R package Zmix, which can currently be applied to univariate Gaussian mixture models.

Chemical and source characterisation of size-segregated urban air particulate matter

Recent epidemiological studies have shown a consistent association of the mass concentration of urban air thoracic (PM10) and fine (PM2.5) particles with mortality and morbidity among cardiorespiratory patients. However, the chemical characteristics of different particulate size ranges and the biological mechanisms responsible for these adverse health effects are not well known. The principal aims of this thesis were to validate a high volume cascade impactor (HVCI) for the collection of particulate matter for physicochemical and toxicological studies, and to make an in-depth chemical and source characterisation of samples collected during different pollution situations. The particulate samples were collected with the HVCI, virtual impactors and a Berner low pressure impactor in six European cities: Helsinki, Duisburg, Prague, Amsterdam, Barcelona and Athens. The samples were analysed for particle mass, common ions, total and water-soluble elements as well as elemental and organic carbon. Laboratory calibration and field comparisons indicated that the HVCI can provide a unique large capacity, high efficiency sampling of size-segregated aerosol particles. The cutoff sizes of the recommended HVCI configuration were 2.4, 0.9 and 0.2 μm. The HVCI mass concentrations were in a good agreement with the reference methods, but the chemical composition of especially the fine particulate samples showed some differences. This implies that the chemical characterization of the exposure variable in toxicological studies needs to be done from the same HVCI samples as used in cell and animal studies. The data from parallel, low volume reference samplers provide valuable additional information for chemical mass closure and source assessment. The major components of PM2.5 in the virtual impactor samples were carbonaceous compounds, secondary inorganic ions and sea salt, whereas those of coarse particles (PM2.5-10) were soil-derived compounds, carbonaceous compounds, sea salt and nitrate. The major and minor components together accounted for 77-106% and 77-96% of the gravimetrically-measured masses of fine and coarse particles, respectively. Relatively large differences between sampling campaigns were observed in the organic carbon content of the PM2.5 samples as well as the mineral composition of the PM2.5-10 samples. A source assessment based on chemical tracers suggested clear differences in the dominant sources (e.g. traffic, residential heating with solid fuels, metal industry plants, regional or long-range transport) between the sampling campaigns. In summary, the field campaigns exhibited different profiles with regard to particulate sources, size distribution and chemical composition, thus, providing a highly useful setup for toxicological studies on the size-segregated HVCI samples.

Bayesian parameter identification in dynamic state space models using modified measurement equations

When Markov chain Monte Carlo (MCMC) samplers are used in problems of system parameter identification, one would face computational difficulties in dealing with large amount of measurement data and (or) low levels of measurement noise. Such exigencies are likely to occur in problems of parameter identification in dynamical systems when amount of vibratory measurement data and number of parameters to be identified could be large. In such cases, the posterior probability density function of the system parameters tends to have regions of narrow supports and a finite length MCMC chain is unlikely to cover pertinent regions. The present study proposes strategies based on modification of measurement equations and subsequent corrections, to alleviate this difficulty. This involves artificial enhancement of measurement noise, assimilation of transformed packets of measurements, and a global iteration strategy to improve the choice of prior models. Illustrative examples cover laboratory studies on a time variant dynamical system and a bending-torsion coupled, geometrically non-linear building frame under earthquake support motions. (C) 2015 Elsevier Ltd. All rights reserved.

A temporal and spatial study of invertebrate communities associated with hard-bottom habitats in the South Atlantic Bight

Species composition, biomass, density, and diversity of benthic invertebrates from six bard-bottom areas were evaluated. Seasonal collections using a dredge, trawl, and suction and grab samplers yielded 432, 525, and 845 taxa, respectively. Based on collections wltb the different gear types, species composition of invertebrates was found to change bathymetrically. Inner- and mlddle-shelf sites were more similar to each other in terms of invertebrate species composition than they were to outer-shelf sites, regardless of season. Sites on the inner and outer shelf were grouped according to latitude; however, results suggest that depth is apparently a more important determinant of invertebrate species composition than either season or latitude. Sponges generally dominated dredge and trawl collections in terms of biomass. Generally, cnidarians, bryozoans, and sponges dominated at sites In terms of number of taxa collected. The most abundant smaller macrofauna collected in suction and grab samples were polychaetes, amphipods, and mollusks. Densities of the numerically dominant species changed botb seasonally and bathymetrically, with very few of these species restricted to a specific bathymetrlc zone. The high diversity of invertebrates from hard-bottom sites is attributed to the large number of rare species. No consistent seasonal changes in diversity or number of species were noted for individual stations or depth zones. In addition, H and its components showed no definite patterns related to depth or latitude. However, more species were collected at middle-shelf sites than at inner- or outer-shelf sites, which may be related to more stable bottom temperature or greater habitat complexity in that area. (PDF file contains 110 pages.)

Biological Platforms for Environmental Sensor technologies and their uses as indicators of the marine environment, Seward, Alaska, September 19-21, 2007: workshop proceedings

The Alliance for Coastal Technologies (ACT) Workshop entitled, "Biological Platforms as Sensor Technologies and their Use as Indicators for the Marine Environment" was held in Seward, Alaska, September 19 - 21,2007. The workshop was co-hosted by the University of Alaska Fairbanks (UAF) and the Alaska SeaLife Center (ASLC). The workshop was attended by 25 participants representing a wide range of research scientists, managers, and manufacturers who develop and deploy sensory equipment using aquatic vertebrates as the mode of transport. Eight recommendations were made by participants at the conclusion of the workshop and are presented here without prioritization: 1. Encourage research toward development of energy scavenging devices of suitable sizes for use in remote sensing packages attached to marine animals. 2. Encourage funding sources for development of new sensor technologies and animal-borne tags. 3. Develop animal-borne environmental sensor platforms that offer more combined systems and improved data recovery methodologies, and expand the geographic scope of complementary fixed sensor arrays. 4. Engage the oceanographic community by: a. Offering a mini workshop at an AGU ocean sciences conference for people interested in developing an ocean carbon program that utilizes animal-borne sensor technology. b. Outreach to chemical oceanographers. 5. Min v2d6.sheepserver.net e and merge technologies from other disciplines that may be applied to marine sensors (e.g. biomedical field). 6. Encourage the NOAA Permitting Office to: a. Make a more predictable, reliable, and consistent permitting system for using animal platforms. b. Establish an evaluation process. c. Adhere to established standards. 7. Promote the expanded use of calibrated hydrophones as part of existing animal platforms. 8. Encourage the Integrated Ocean Observing System (IOOS) to promote animal tracking as effective samplers of the marine environment, and use of animals as ocean sensor technology platforms. [PDF contains 20 pages]

Oceanographic Profiling Observations MOCE-4 Cruise: 26 January to 12 February 1998

This report contains results from the fourth cruise of the MODIS Optical Characterization Experiment (MOCE). Also resented are oceanographic data from two MOBY maintenance cruises L-20 and L-25. The MOCE4 cruise was the first NOAAINESDIS-Ied SeaWiFS Initialization cruise during which a variety ofspectroradiometric observations ofthe upper water column and atmosphere were made by investigators from NOAA, the University of Miami, CHORS and MLML. Data presented in this report were obtained by oceanographic CTD profiler: salinity, temperature, dissolved oxygen, beam attenuation and chlorophyll-a fluorescence~ and by water samplers: total suspended matter and suspended organic carbon and nitrogen, salinity and dissolved oxygen. (PDF contains 142 pages).

Oceanographic Profiling Observations from the MOBY-L7 Cruise: 25 to 30 June 1994

This report contains CTD profiling results from the seventh cruise to the Marine Optics Buoy (MOBY) site near the Island of Lanai. Data presented here were obtained on the University of Hawaii Research Vessel Moana Wave between 26 and 30 June 1994. Two types of data are reported: vertical profile observations of salinity, temperature beam attenuation and chlorophyll-a fluorescence, profiles; and total suspended matter and suspended organic carbon and nitrogen taken from water samplers at those stations.

Oceanographic Profiling Observations from the MOCE-3 Cruise: 27 October to 15 November 1994

This report contains results from the third cruise of the Marine Optical Characterization Experiment (Fig. 1). A variety of spectroradiometric observations of the upper water column and atmosphere were made by investigators from the University of Miami, NOAA, CHORS and MLML. Data presented here were obtained by oceanographic CTD profiler: salinity, temperatllre, dissolved oxygen, beam attenuation and chlorophyll-a fluorescence; and by water samplers: total suspended matter and suspended organic carbon and nitrogen, salinity, and dissolved oxygen.

The deep ocean density structure at the Last Glacial Maximum : What was it and why?

The search for reliable proxies of past deep ocean temperature and salinity has proved difficult, thereby limiting our ability to understand the coupling of ocean circulation and climate over glacial-interglacial timescales. Previous inferences of deep ocean temperature and salinity from sediment pore fluid oxygen isotopes and chlorinity indicate that the deep ocean density structure at the Last Glacial Maximum (LGM, approximately 20,000 years BP) was set by salinity, and that the density contrast between northern and southern sourced deep waters was markedly greater than in the modern ocean. High density stratification could help explain the marked contrast in carbon isotope distribution recorded in the LGM ocean relative to that we observe today, but what made the ocean's density structure so different at the LGM? How did it evolve from one state to another? Further, given the sparsity of the LGM temperature and salinity data set, what else can we learn by increasing the spatial density of proxy records?

We investigate the cause and feasibility of a highly and salinity stratified deep ocean at the LGM and we work to increase the amount of information we can glean about the past ocean from pore fluid profiles of oxygen isotopes and chloride. Using a coupled ocean--sea ice--ice shelf cavity model we test whether the deep ocean density structure at the LGM can be explained by ice--ocean interactions over the Antarctic continental shelves, and show that a large contribution of the LGM salinity stratification can be explained through lower ocean temperature. In order to extract the maximum information from pore fluid profiles of oxygen isotopes and chloride we evaluate several inverse methods for ill-posed problems and their ability to recover bottom water histories from sediment pore fluid profiles. We demonstrate that Bayesian Markov Chain Monte Carlo parameter estimation techniques enable us to robustly recover the full solution space of bottom water histories, not only at the LGM, but through the most recent deglaciation and the Holocene up to the present. Finally, we evaluate a non-destructive pore fluid sampling technique, Rhizon samplers, in comparison to traditional squeezing methods and show that despite their promise, Rhizons are unlikely to be a good sampling tool for pore fluid measurements of oxygen isotopes and chloride.