Carbon and nitrogen mineralization in Vertisol as mediated by type and placement method of residue

Selection of appropriate residue application method is essential for better use of biomass for soil and environmental health improvement. A laboratory incubation experiment was conducted for 75 days to investigate C and N mineralization of residues of soybean (Glycine max L.), chickpea (Cicer arietinum L.), maize (Zea mays L.), and wheat (Triticum aestivum L.) placed on the soil surface and incorporated into the soil. The residue of soybean and chickpea had a greater decomposition rate than that of maize and wheat, despite of their placements. Higher rate of decomposition of the residue of soybean and chickpea was recorded when it was kept on the soil surface while soil incorporation of residue of wheat and maize resulted in faster decomposition. Therefore, these findings could be used as guidelines for management of crop residue application in farmland to improve soil and environmental quality.     

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.     

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.     

Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river

Rapid urban development has led to a critical negative impact on water bodies flowing in and around urban areas. In the present study, 25 physiochemical and biological parameters have been studied on water samples collected from the entire section of a small river originating and ending within an urban area. This study envisaged to assess the water quality status of river body and explore probable sources of pollution in the river. Weighted arithmetic water quality index (WQI) was employed to evaluate the water quality status of the river. Multivariate statistical techniques namely cluster analysis (CA) and principal component analysis (PCA) were applied to differentiate the sources of variation in water quality and to determine the cause of pollution in the river. WQI values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. Cluster analysis results showed that the river samples can be divided into four groups. Use of PCA identified four important factors describing the types of pollution in the river, namely (1) mineral and nutrient pollution, (2) heavy metal pollution, (3) organic pollution, and (4) fecal contamination. The deteriorating water quality of the river was demonstrated to originate from wide sources of anthropogenic activities, especially municipal sewage discharge from unplanned housing areas, wastewater discharge from small industrial units, livestock activities, and indiscriminate dumping of solid wastes in the river. Thus, the present study effectively demonstrates the use of WQI and multivariate statistical techniques for gaining simpler and meaningful information about the water quality of a lotic water body as well as to identify of the pollution sources.     

Trace metals in soil and leaves of Jacaranda mimosifolia in Tshwane area,South Africa

Plant and soil have been identified as major sink of pollutants in the environment. We evaluated the reliability of biomonitoring of heavy metals in Tshwane area with the use of leaves of Jacaranda mimosifolia. The concentrations of heavy metals such as Ca, Mg, Fe, Pb, Zn, Cu, Sb were measured in leaves of J. mimosifolia and soils collected from 10 sites in the city of Tshwane during two sampling periods. The metals were analyzed with the use of ICP-MS. The result shows significant differences in the concentration of trace metals in all the sites (p < 0.01). The differences between the two sampling periods were statistically significant (p < 0.01). Concentration of metals from high traffic and industrial sites were significantly higher than in the residential areas (p < 0.01). Concentration factor suggests that translocation of metals from roots to leaves could be relevant only for some metals such as Ca, Mg and Sb. The study reveals an anthropogenic source for the trace metals. Leaves of J. mimosifolia were found to be a useful biomonitor of the determined trace metals.     

The seasonal cycles and photochemistry of C2–C5 alkanes at Mace Head

Continuous in-situ measurements of NMHCs at Mace Head, Ireland during two full annual cycles from January 2005 to January 2007 were used to investigate NMHC emission sources and transport including dilution and photochemical oxidation. The Mace Head research station is ideally located to sample a wide range of air masses including polluted European transport, clean North Atlantic and Arctic air masses and the ultra-clean, Southern Atlantic air masses. The variety in air mass sampling is used to investigate interaction of emissions, transport, dilution and photochemistry. Variability of long-lived hydrocarbon ratios is used to assess and estimate typical transport times from emission source to the Mace Head receptor. Seasonality in the ratios of isomeric alkane pairs (for butane and pentanes) are used to assess the effects of atmospheric transport and photochemical ageing. Finally, the natural logarithms of NMHC ratios are used to assess photochemical oxidation.     

Influence of boundary conditions on CMAQ simulations over the Iberian Peninsula

The influence of chemical boundary conditions (BC) on the response of the Community Multiscale Air Quality (CMAQ) model over the Iberian Peninsula was investigated in this study. Three strategies to supply boundary conditions in the context of the Integrated Assessment Modelling System for the Iberian Peninsula (SIMCA) were tested. Alternative methods consist in providing BC from (1) fixed, time-independent, concentration profiles, (2) concentrations predicted in a CMAQ mother domain (48 km, 1 h resolution) and (3) concentration values from the GEOS-Chem chemical-transport global model (2 × 2.5°, 3 h resolution). High resolution (3 km) simulated concentrations of the main pollutants (NO₂, NO, SO₂, O₃, PM₁₀ and PM_2.5) were compared through a comprehensive statistical analysis including observational data from 165 monitoring stations all over the Iberian Peninsula. It was found that model sensitivity to BC for nitrogen and sulphur oxides was limited, being restricted to the vicinity of model boundaries. However, significant domain-wide differences were found when modelling ozone and PM depending on the BC provided to run the tests. Although model performance was affected by spatial and seasonal factors, the results indicate that model-derived, dynamic BC improved CMAQ predictions when compared to those based on static concentrations prescribed in the boundaries. Aggregated statistics suggest that the GEOS-Chem produced the best results for O₃ and PM_2.5 while NO₂ and PM₁₀ were slightly better predicted under the CMAQ nesting approach. Besides the statistical evaluation some other relevant issues in the context of Integrated Assessment Modelling (IAM) are discussed to gain a better insight into the suitability of the methods analyzed and limitations of downscaling methods. Despite being useful to get a better understanding of the role of BC in SIMCA, this study contributed to highlight model deficiencies and therefore to point out future research needs to improve IAM activities in the Iberian Peninsula.     

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.     

Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks

The Minnesota Particulate Matter 2.5 (PM_2.5) Source Apportionment Study was undertaken to explore the utility of PM_2.5 mass, element, ion, and carbon measurements from long-term speciation networks for pollution source attribution. Ambient monitoring data at eight sites across the state were retrieved from the archives of the Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and analyzed by an Effective Variance – Chemical Mass Balance (EV-CMB) receptor model with region-specific geological source profiles developed in this study. PM_2.5 was apportioned into contributions of fugitive soil dust, calcium-rich dust, taconite (low grade iron ore) dust, road salt, motor vehicle exhaust, biomass burning, coal-fired utility, and secondary aerosol. Secondary sulfate and nitrate contributed strongly (49–71% of PM_2.5) across all sites and was dominant (≥60%) at IMPROVE sites. Vehicle exhausts accounted for 20–70% of the primary PM_2.5 contribution, largely exceeding the proportion in the primary PM_2.5 emission inventory. The diesel exhaust contribution was separable from the gasoline engine exhaust contribution at the STN sites. Higher detection limits for several marker elements in the STN resulted in non-detectable coal-fired boiler contributions which were detected in the IMPROVE data. Despite the different measured variables, analytical methods, and detection limits, EV-CMB results from a nearby IMPROVE-STN non-urban/urban sites showed similar contributions from regional sources – including fugitive dust and secondary aerosol. Seasonal variations of source contributions were examined and extreme PM_2.5 episodes were explained by both local and regional pollution events.