Feasibility of coupling a thermal/optical carbon analyzer to a quadrupole mass spectrometer for enhanced PM2.5 speciation

A thermal/optical carbon analyzer (TOA), normally used for quantification of organic carbon (OC) and elemental carbon (EC) in PM_2.5 (fine particulate matter) speciation networks, was adapted to direct thermally evolved gases to an electron impact quadrupole mass spectrometer (QMS), creating a TOA-QMS. This approach produces spectra similar to those obtained by the Aerodyne aerosol mass spectrometer (AMS), but the ratios of the mass to charge (m/z) signals differ and must be remeasured using laboratory-generated standards. Linear relationships are found between TOA-QMS signals and ammonium (NH₄⁺), nitrate (NO₃^?), and sulfate (SO₄^2-) standards. For ambient samples, however, positive deviations are found for SO₄^2-, compensated by negative deviations for NO₃^?, at higher concentrations. This indicates the utility of mixed-compound standards for calibration or separate calibration curves for low and high ion concentrations. The sum of the QMS signals across all m/z after removal of the NH₄⁺, NO₃^?, and SO₄^2- signals was highly correlated with the carbon content of oxalic acid (C?H?O?) standards. For ambient samples, the OC derived from the TOA-QMS method was the same as the OC derived from the standard IMPROVE_A TOA method. This method has the potential to reduce complexity and costs for speciation networks, especially for highly polluted urban areas such as those in Asia and Africa.

Implications: Ammonium, nitrate, and sulfate can be quantified by the same thermal evolution analysis applied to organic and elemental carbon. This holds the potential to replace multiple parallel filter samples and separate laboratory analyses with a single filter and a single analysis to account for a large portion of the PM_2.5 mass concentration.     

A multivariate examination of ‘artificial mussels’ in conjunction with spot water tests in freshwater ecosystems

Metal pollution in aquatic systems is considered a serious environmental issue globally due to their ability to accumulate in aquatic environments. Wetlands are vulnerable to this pollution as they are known to trap toxins, removing them from the water. Artificial mussel technology, originally developed for marine environments, was applied to this freshwater system and spot water samples were collected. The Nyl River floodplain (Ramsar classified) is one of the largest and most ecologically significant wetlands in South Africa. The aims of this study were to determine metal contamination along the Nyl River system by means of artificial mussels (AM) and water ICP-MS analysis and to determine whether the use of AMs in conjunction with spot water testing could give more insight into the pollution in freshwater wetlands. The concentrations of Al, Cd, Cr, Co, Cu, Fe, Mn, Ni, Pb and Zn were determined at seven sites. It was determined that the levels accumulated by the AMs differed in spatial and temporal trends when compared to spot water samples. It was determined that there were high levels of some metals found in the spot water tests that were not corroborated by the AMs results, which could indicate isolated pollution events. The use of AMs in conjunction with spot water testing was determined to be beneficial in gaining deeper insight into water metal conditions in dynamic freshwater systems.     

Pre-incubation in soil improves the nitrogen fertiliser value of hair waste

Global generation of human hair waste and its disposal at landfills could contribute to the leaching of nitrates into ground water. High concentrations of nitrogen (N) and other elements suggest that the waste could be a source of plant nutrients and differences in ethnic hair types could affect nutrient release and fertiliser value. The objective of this study was to determine the effects of hair type, as an N source, and pre-incubation time on dry-matter yield, nutrient uptake by spinach (Spinacia oleracea L.) and residual soil nutrients. Salons in Pietermaritzburg provided bulk African and Caucasian hair waste, without distinguishing age, sex, health status or livelihood of the individuals. The hair waste was analysed for elemental composition. A pot experiment was set up under glasshouse conditions. The hair waste was incorporated (400 kg N ha^?1) into a loamy oxisol and pre-incubated for 0, 28, 56 and 84 days before planting spinach. Potassium (K) and phosphorus (P) were corrected to the same level for all treatments. Spinach seedlings were then cultivated for 6 weeks. Shoot dry-matter and the uptake of all nutrients, except P, were increased by the pre-incubation of hair. African hair pre-incubated for 28 days resulted in greater dry-matter, N, K, Mn and S uptake than Caucasian hair. Increasing pre-incubation resulted in a decline in the residual soil pH and exchangeable K. The findings suggested that pre-incubation improves the N fertiliser value of hair and that African hair has greater value than Caucasian hair when pre-incubated for a short period.     

The probabilistic tsunami hazard assessment along Karnataka Coast from Makran Subduction Zone,west coast of India

Coastal tsunami amplitudes were calculated to identify areas susceptible to tsunami hazard at selected locations of the coast of Karnataka, west of India, due to earthquakes in the Makran Subduction Zone. This is the first time that the probabilistic tsunami hazard assessment along this study area has been attempted. A series of earthquake source scenarios with magnitudes of Mw 8.0, Mw 8.5, and a mega thrust of Mw 9.1 were modeled by using the Community Model Interface for Tsunami interface with the MOST model of Titov and Synolakis (J. Waterway, Port, Coastal and Ocean Engineering, 121(6), 308–316, 1995). As per the previous occurrences, the two least magnitudes are probable, while Mw 9.1 is a worst-case scenario as described by Heidarzadeh et al. (Ocean Engineering, 36(5), 368–376, 2009) and the same is reported by Burbidge et al. (Geoscience Australia Professional Opinion No. 2009/11) as high magnitude. These are not at all historical earthquakes or specifically from historical catalogues. The results of modeling show that all the seven coastal locations are inundated barely in our worst-case scenario with maximum water levels in the range of 100–200 cm. The first tsunami wave strikes the coast within 4–5 h of earthquake occurrence.     

Real<Emphasis Type="Bold">-</Emphasis>time water quality monitoring using Internet of Things in SCADA

Water pollution is the root cause for many diseases in the world. It is necessary to measure water quality using sensors for prevention of water pollution. However, the related works remain the problems of communication, mobility, scalability, and accuracy. In this paper, we propose a new Supervisory Control and Data Acquisition (SCADA) system that integrates with the Internet of Things (IoT) technology for real-time water quality monitoring. It aims to determine the contamination of water, leakage in pipeline, and also automatic measure of parameters (such as temperature sensor, flow sensor, color sensor) in real time using Arduino Atmega 368 using Global System for Mobile Communication (GSM) module. The system is applied in the Tirunelveli Corporation (Metro city of Tamilnadu state, India) for automatic capturing of sensor data (pressure, pH, level, and energy sensors). SCADA system is fine-tuned with additional sensors and reduced cost. The results show that the proposed system outperforms the existing ones and produces better results. SCADA captures the real-time accurate sensor values of flow, temperature, and color and turbidity through the GSM communication.     

Urban tracer dispersion experiments during the second DAPPLE field campaign in London 2004

As part of the DAPPLE programme two large scale urban tracer experiments using multiple simultaneous releases of cyclic perfluoroalkanes from fixed location point sources was performed. The receptor concentrations along with relevant meteorological parameters measured are compared with a three screening dispersion models in order to best predict the decay of pollution sources with respect to distance. It is shown here that the simple dispersion models tested here can provide a reasonable upper bound estimate of the maximum concentrations measured with an empirical model derived from field observations and wind tunnel studies providing the best estimate. An indoor receptor was also used to assess indoor concentrations and their pertinence to commonly used evacuation procedures.     

Assessment of the uncertainty of using an inverse-dispersion technique to measure methane emissions from animals in a barn and in a small pen

Dispersion techniques are useful for assessing the effectiveness of management practices in mitigating methane (CH₄) emissions from animal operations. In this paper, the accuracy of an inverse-dispersion technique was examined for two common situations: 1) emissions from animals in a barn and 2) emissions from animals in a pen. For both situations, the accuracy of emission estimates generally increased with increasing fetch (scaled to barn height, h, or to pen width, X_s) between the source and the concentration measurement. The gas recovery ratio increased from 0.66 at 5 h to 0.93–1.03 at 10 h–25 h for the barn, and decreased from 1.59 at 0 X_s to 0.99 at 5 X_s and from 1.54 at 0 X_s to 1.09 at 5 X_s for the two small pen scenarios, due to the declining sensitivity of the dispersion model to errors in wind complexity and errors in the assumed source configuration. However, the relative uncertainty of the measured concentration increased with fetch due to the decreasing gas concentrations. Hence, improving the accuracy of emission estimates is a compromise between the source configuration sensitivity and the concentration measurement sensitivity. Fetches of about twice the size of the pen and about 10 times the height of the barn are suggested.     

Verification of diffusive and pumped samplers for volatile organic compounds using a controlled atmosphere test facility

There is a requirement to verify the performance of sorbent-based passive or active samplers and to extend their use, where possible, to monitor volatile organic compounds (VOCs) that are known to be photochemical ozone pre-cursors or are relevant to the activities of the petrochemical industry. We report measurements of the 14-day diffusive uptake rates for the VOCs: i-butane (2-methyl propane), n-butane, i-pentane (2-methyl butane), n-pentane, n-hexane, benzene, toluene, and m-xylene (at environmental level concentrations) for industry standard axial samplers (Perkin–Elmer-type samplers) containing the sorbents Carbopack-X, -Z, -B or Tenax-TA. We also present data on back-diffusion, blank levels, and storage for the above sorbents, and describe the simultaneous use of the sorbent Carbopack-X for pumped sampling of certain VOCs. The results were obtained by dosing samplers in a controlled atmosphere test facility (CATFAC) operating under well-defined conditions of concentration, nominal temperature of 20 °C, wind speed of 0.5 m s^?1, and relative humidities of 0% and 80%. Field measurements were also obtained to provide supplementary data to support the laboratory study. Results are compared to existing published data, where these are available.     

Assimilation of conventional and satellite wind observations in a mesoscale atmospheric model for studying atmospheric dispersion

A mesoscale atmospheric model PSU/NCAR MM5 is used to provide operational weather forecasts for a nuclear emergency response decision support system on the southeast coast of India. In this study the performance of the MM5 model with assimilation of conventional surface and upper-air observations along with satellite derived 2-d surface wind data from QuickSCAT sources is examined. Two numerical experiments with MM5 are conducted: one with static initialization using NCEP FNL data and second with dynamic initialization by assimilation of observations using four dimensional data assimilation (FDDA) analysis nudging for a pre-forecast period of 12 h. Dispersion simulations are conducted for a hypothetical source at Kalpakkam location with the HYSPLIT Lagrangian particle model using simulated wind field from the above experiments. The present paper brings out the differences in the atmospheric model predictions and the differences in dispersion model results from control and assimilation runs. An improvement is noted in the atmospheric fields from the assimilation experiment which has led to significant alteration in the trajectory positions, plume orientation and its distribution pattern. Sensitivity tests using different PBL and surface parameterizations indicated the simple first order closure schemes (Blackadar, MRF) coupled with the simple soil model have given better results for various atmospheric fields. The study illustrates the impact of the assimilation of the scatterometer wind and automated weather stations (AWS) observations on the meteorological model predictions and the dispersion results.