Deriving fuel-based emission factor thresholds to interpret heavy-duty vehicle roadside plume measurements

Remote sensing devices have been used for decades to measure gaseous emissions from individual vehicles at the roadside. Systems have also been developed that entrain diluted exhaust and can also measure particulate matter (PM) emissions. In 2015, the California Air Resources Board (CARB) reported that 8% of in-field diesel particulate filters (DPF) on heavy-duty (HD) vehicles were malfunctioning and emitted about 70% of total diesel PM emissions from the DPF-equipped fleet. A new high-emitter problem in the heavy-duty vehicle fleet had emerged. Roadside exhaust plume measurements reflect a snapshot of real-world operation, typically lasting several seconds. In order to relate roadside plume measurements to laboratory emission tests, we analyzed carbon dioxide (CO₂), oxides of nitrogen (NO_X), and PM emissions collected from four HD vehicles during several driving cycles on a chassis dynamometer. We examined the fuel-based emission factors corresponding to possible exceedances of emission standards as a function of vehicle power. Our analysis suggests that a typical HD vehicle will exceed the model year (MY) 2010 emission standards (of 0.2 g NO_X/bhp-hr and 0.01 g PM/bhp-hr) by three times when fuel-based emission factors are 9.3 g NO_X/kg fuel and 0.11 g PM/kg using the roadside plume measurement approach. Reported limits correspond to 99% confidence levels, which were calculated using the detection uncertainty of emissions analyzers, accuracy of vehicle power calculations, and actual emissions variability of fixed operational parameters. The PM threshold was determined for acceleration events between 0.47 and 1.4 mph/sec only, and the NO_X threshold was derived from measurements where after-treatment temperature was above 200°C. Anticipating a growing interest in real-world driving emissions, widespread implementation of roadside exhaust plume measurements as a compliment to in-use vehicle programs may benefit from expanding this analysis to a larger sample of in-use HD vehicles.

Implications: Regulatory agencies, civil society, and the public at large have a growing interest in vehicle emission compliance in the real world. Leveraging roadside plume measurements to identify vehicles with malfunctioning emission control systems is emerging as a viable new and useful method to assess in-use performance. This work proposes fuel-based emission factor thresholds for PM and NOx that signify exceedances of emission standards on a work-specific basis by analyzing real-time emissions in the laboratory. These thresholds could be used to prescreen vehicles before roadside enforcement inspection or other inquiry, enhance and further develop emission inventories, and potentially develop new requirements for heavy-duty inspection and maintenance (I/M) programs, including but not limited to identifying vehicles for further testing.     

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.     

Organochlorine contaminants in the Vistula Lagoon sedimentation zone as possible source of lagoon recontamination

The presented results include decade of monitoring of the Vistula Lagoon waters and have been supplemented by the determination of chlorinated compounds, as well as on concentrations of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) in the sedimentation zone. Monitoring of river waters entering the Polish part of the lagoon and the lagoon waters confirmed the presence of plant protection chemical; the largest contributors has lindane (34%) and DDT_total (21%); the same as for sediments were dominate lindane (19%) and DDT_total (14%) within pp-DDT isomer dominate (13%). In the lagoon water, PCDD/Fs were determined within a range of 1.5–5.6 ng dm^?3, leading to average toxicity of 0.18?±?0.13 ng TEQ·dm^?3. In sediments, their concentrations fell within a range of 22.7–405.7 ng kg^?1 dw and the average toxicity of the lagoon sediments was set at 5.00?±?1.98 ng TEQ·kg^?1 dw. Both in water and sediments, the greatest share among PCDD/Fs has octa-chlorodibenzodioxin. Due to the hydromorphological conditions of the lagoon, the waters are mixed to the bottom causing the surface layer of sediment to become remobilized—this is suggested as the key factor when it comes to water recontamination and increased access of POPs to marine organisms.     

Pond bank access as an approach for managing toxic cyanobacteria in beef cattle pasture drinking water ponds

Forty-one livestock drinking water ponds in Alabama beef cattle pastures during were surveyed during the late summer to generally understand water quality patterns in these important water resources. Since livestock drinking water ponds are prone to excess nutrients that typically lead to eutrophication, which can promote blooms of toxigenic phytoplankton such as cyanobacteria, we also assessed the threat of exposure to the hepatotoxin, microcystin. Eighty percent of the ponds studied contained measurable microcystin, while three of these ponds had concentrations above human drinking water thresholds set by the US Environmental Protection Agency (i.e., 0.3 μg/L). Water quality patterns in the livestock drinking water ponds contrasted sharply with patterns typically observed for temperate freshwater lakes and reservoirs. Namely, we found several non-linear relationships between phytoplankton abundance (measured as chlorophyll) and nutrients or total suspended solids. Livestock had direct access to all the study ponds. Consequently, the proportion of inorganic suspended solids (e.g., sediment) increased with higher concentrations of total suspended solids, which underlies these patterns. Unimodal relationships were also observed between microcystin and phytoplankton abundance or nutrients. Euglenoids were abundant in the four ponds with chlorophyll concentrations >?250 μg/L (and dominated three of these ponds), which could explain why ponds with high chlorophyll concentrations would have low microcystin concentrations. Based on observations made during sampling events and available water quality data, livestock-mediated bioturbation is causing elevated total suspended solids that lead to reduced phytoplankton abundance and microcystin despite high concentrations of nutrients, such as phosphorus and nitrogen. Thus, livestock could be used to manage algal blooms, including toxic secondary metabolites, in their drinking water ponds by allowing them to walk in the ponds to increase turbidity.     

Impact of artificial lagoons on seawater quality: evidence from 7 years of physicochemical seawater monitoring

Seven years (2010–2016) of data on the basic physicochemical properties of seawater, temperature, salinity, dissolved oxygen (DO), nutrients, chlorophyll a (Chl a), and hydrocarbons from two lagoons were used to evaluate the impact of the anthropogenic activities inside the lagoon on the water quality and to explore the relationship of any impact from the lagoons’ design. Statistical analysis shows the modification in water quality inside the lagoon compared to the ambient seawater is particularly evident for nitrate, silicate, and Chl a. The modification is attributed to the extensive boat activities in the lagoons and the limited water exchange between the lagoons and ambient seawater. However, the impact to both lagoons is generally limited to inside the lagoons. The oligotrophic state of the two lagoons was evaluated and it was found that the most marked code violations were found in DIN inside both lagoons. In order to explore the design importance, the water exchange and overall water quality was compared between the two lagoons. This study highlights the importance of an environmental design study before the construction of any lagoon project. Proper design would maintain acceptable water quality inside the lagoons, critical for environmental health and supporting continued recreational activities.     

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.     

An automated (novel) algorithm for estimating green vegetation cover fraction from digital image: UIP-MGMEP

Green vegetation cover fraction (VCF) is an important indicator of vegetation status in ecology and agronomy. Digital image analysis (DIA) has been widely accepted as a new VCF measurement technique. In this study, we present a novel fully automatic threshold segmentation algorithm for VCF measurements, which is named as upper inflection point plus mean gradient magnitude of edge pixels (UIP-MGMEP). The algorithm performs VCF estimation upon the vegetation index Excess Green (EXG). UIP-MGMEP optimizes the EXG threshold by searching the upper inflection point (UIP) of the M-Et curve (mean gradient magnitude of edge pixels (MGMEP) vs. EXG threshold), based on the assumption that EXG variance of the boundary pixels between vegetation and background is larger than the variance of the background. Five typical sample images are used to illustrate how ground complexity reduces the distinctness of the UIP. Three controlled experiments are illustrated to test the robustness of UIP-MGMEP to resolution, exposure, and ground complexity. The results show that UIP-MGMEP is a promising algorithm for automatic VCF estimation upon digital images. Compared to broad-leaved grass, narrow-leaved grass is more sensitive to resolution and exposure. To reduce ground complexity, smaller footprint size while more images to cover the same area may be better than one image with large footprint size. UIP-MGMEP is fully automatic, making it promising for batch processing of VCF measurements that is very difficult in any wide-range field survey in the past. UIP-MGMEP algorithm can only extract green vegetation and is not suitable for non-green (even grayish-green) vegetation, due to the limits of vegetation index EXG. In addition, UIP-MGMEP is not recommended for images with VCF less than 0.5% or greater than 99.5%.     

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.