Conservation agricultural practices for minimizing ammonia volatilization and maximizing wheat productivity

Environmental Science and Pollution Research - A large amount of ammonia volatilization from the agricultural system causes environmental problems and increases production costs. Conservation...     

Nitrate contamination in water resources,human health risks and its remediation through adsorption: a focused review

The level of nitrate in water has been increasing considerably all around the world due to vast application of inorganic nitrogen fertiliser and animal manure. Because of nitrate’s high solubility in water, human beings are getting exposed to it mainly through various routes including water, food etc. Various regulations have been set for nitrate (45–50 mgNO₃^?/L) in drinking water to protect health of the infants from the methemoglobinemia, birth defects, thyroid disease, risk of specific cancers, i.e. colorectal, breast and bladder cancer caused due to nitrate poisoning. Different methods like ion exchange, adsorption, biological denitrification etc. have the ability to eliminate the nitrate from the aqueous medium. However, adsorption process got preference over the other approaches because of its simple design and satisfactory results especially with surface modified adsorbents or with mineral-based adsorbents. Different types of adsorbents have been used for this purpose; however, adsorbents derived from the biomass wastes have great adsorption capacities for nitrate such as tea waste-based adsorbents (136.43 mg/g), carbon nanotube (142.86 mg/g), chitosan beads (104 mg/g) and cetyltrimethylammonium bromide modified rice husk (278 mg/g). Therefore, a thorough literature survey has been carried out to formulate this review paper to understand various sources of nitrate pollution, route of exposure to the human beings, ill effects along with discussing the key developments as well as the new advancements reported in procuring low-cost efficient adsorbents for water purification.

     

Developing an effectiveness index for biomedical waste management in Indian states using a composite indicators approach

Environmental Science and Pollution Research - The waste from healthcare facilities (HCFs) is most devastating as they induce health hazards and pollute the environment. The effective management of...     

An Analysis of the Annual and Seasonal Trends of Air Quality Index of Delhi

The Air Quality Index (AQI) is an index for reporting daily air quality. A study on the annual and seasonal variations of Air Quality Index over a period of 9 years (1996-2004) based on daily averaged concentration data of criteria air pollutants has been conducted for Delhi. An attempt has been made to quantify the changes in the AQI on annual and seasonal (winter, summer, monsoon and post monsoon) basis for 9 years. Measurements for the seven monitoring sites (Nizamuddin, Ashok Vihar, Shahzada Baug, Shahadara, Janakpuri, Sirifort and ITO) in Delhi were analysed and trends were also compared amongst these sites. Maximum Operator Function method was used to compute the Air Quality Index of the above areas and percentage variations in different severity class is discussed which provides in depth analysis of the trends. The best air quality was depicted by Shahzada Baug followed by Shahdara, both of these were classified as industrial areas indicating that policy measures relating to the industries in the city during past years have helped in improving the air quality. The air quality in other areas have improved slightly in the span of nine years but still remains critical indicating continued rigorous efforts in this direction. Increased traffic density seems to have resulted into the worst air quality at ITO in the city amongst all the monitoring stations. There is a shift for the worst AQI in the city from winter to summer season in a time span of these nine years. Change of season for worst AQI from Winter to Summer may also be likely due to increased photochemical reactions playing major role with change in the nature of emissions imposed due to different control measures such as CNG implementation, significant shift to LPG in domestic sector etc. calling for a detailed study, those which started after the year 2000. After the year 2000, there is a significant increase in the Nitrogen-dioxide (NO(2)) concentration at all stations. ITO which has shown continuous exponential increase in pollution levels has first time showed a declining AQI trend in the year 2004 and one of the contributing factors could have been the Delhi metro (initiated in 2002) passing through congested neighbouring areas causing traffic decongestion here. In general, the areas which are farthest from metro route viz., Siri-fort, Nizamuddin, Janakpuri etc. did not record declining AQI in 2003 onwards as happened with stations closer to Metro route such as Ashok Vihar and ITO. An attempt has been made to quantify the reasons that lead to the changes in the values of the AQI.     

A classification tree based modeling approach for segment related crashes on multilane highways

Introduction

This study presents a classification tree based alternative to crash frequency analysis for analyzing crashes on mid-block segments of multilane arterials.

Method

The traditional approach of modeling counts of crashes that occur over a period of time works well for intersection crashes where each intersection itself provides a well-defined unit over which to aggregate the crash data. However, in the case of mid-block segments the crash frequency based approach requires segmentation of the arterial corridor into segments of arbitrary lengths. In this study we have used random samples of time, day of week, and location (i.e., milepost) combinations and compared them with the sample of crashes from the same arterial corridor. For crash and non-crash cases, geometric design/roadside and traffic characteristics were derived based on their milepost locations. The variables used in the analysis are non-event specific and therefore more relevant for roadway safety feature improvement programs. First classification tree model is a model comparing all crashes with the non-crash data and then four groups of crashes (rear-end, lane-change related, pedestrian, and single-vehicle/off-road crashes) are separately compared to the non-crash cases. The classification tree models provide a list of significant variables as well as a measure to classify crash from non-crash cases. ADT along with time of day/day of week are significantly related to all crash types with different groups of crashes being more likely to occur at different times.

Conclusions

From the classification performance of different models it was apparent that using non-event specific information may not be suitable for single vehicle/off-road crashes.

Impact on Industry

The study provides the safety analysis community an additional tool to assess safety without having to aggregate the corridor crash data over arbitrary segment lengths.     

Transcriptome analysis provides insights for understanding the adverse effects of endosulfan in Drosophila melanogaster

Indiscriminate use of agrochemicals worldwide, particularly, persistent organic pollutants (POPs), is of concern. Endosulfan, a POP, is used by various developing/developed nations and is known to adversely affect the development and the hormonal profiles of humans and animals. However, little is known about the molecular players/pathways underlying the adverse effects of endosulfan. We therefore analyzed the global gene expression changes and subsequent adverse effects of endosulfan using Drosophila. We used Drosophila melanogaster keeping in view of its well annotated genome and the wealth of genetic/molecular reagents available for this model organism. We exposed third instar larvae of D. melanogaster to endosulfan (2.0 μg mL⁻¹) for 24 h and using microarray, we identified differential expression of 256 genes in exposed organisms compared to controls. These genes are associated with cellular processes such as development, stress and immune response and metabolism. Microarray results were validated through quantitative PCR and biochemical assay on a subset of genes/proteins. Taking cues from microarray data, we analyzed the effect of endosulfan on development, emergence and survival of the organism. In exposed organisms, we observed deformities in hind-legs, reminiscent of those observed in higher organisms exposed to endosulfan. In addition, we observed delayed and/or reduced emergence in exposed organisms when compared to their respective controls. Together, our studies not only highlight the adverse effects of endosulfan on the organism but also provide an insight into the possible genetic perturbations underlying these effects, which might have potential implications to higher organisms.     

A review on ex situ mineral carbonation

The increased CO₂ quantities in the environment have led to many harmful effects. Therefore, it is very important to decrease the CO₂ levels in the environment. CO₂ capture along with safe and permanent storage using mineral CO₂ sequestration method can play an important role to reduce carbon emissions into the environment. Mineral sequestration is a stable storage method that provides long-term storage and an appropriate substitute for the more popular geological storage method. The process is most suited for places where there is a lack of underground cavities for underground geological storage. Minerals rich in Ca and Mg are used predominantly in carbonation reactions. In addition, those alkaline wastes that are rich in Mg and Ca such as cement waste, steel slag and many process ashes can also be employed in CO₂ sequestration. Mineral carbonation could be used for the sequestration of billions of tonnes of CO₂ every year. However, various drawbacks related to mineral carbonation still need to be addressed, such as resolving the slow rate of reactions, necessity of large amounts of feedstock, decreasing the high overall cost of CO₂ sequestration and reducing the huge energy requirements to accelerate the carbonation reaction. This study explores a number of carbonation methods, parameters that control the process and future potential applications of carbonated products.

     

Olivine dissolution from Indian dunite in saline water

The rate and mechanism of olivine dissolution was studied using naturally weathered dunite FO_98.21(Mg_1.884Fe_0.391SiO₄) from an Indian source, that also contains serpentine mineral lizardite. A series of batch dissolution experiments were carried out to check the influence of temperature (30–75 ^°C), initial dunite concentration (0.5 and 20 g/L), and salinity (0–35 g/L NaCl) under fixed head space CO₂ pressure (P\(_{\text {CO}_{2}}\) = 1 barg) on dunite dissolution. Dissolved Mg, Si, and Fe concentrations were determined by inductive coupled plasma atomic emission spectroscopy. End-product solids were characterized by scanning electron microscopy and X-ray diffraction. Initially, rates of dissolution of Si and Mg were observed to be in stoichiometric proportion. After 8 h, the dissolution rate was observed to decline. At the end of the experiment (504 h), an amorphous silica-rich layer was observed over the dunite surface. This results in decay of the dissolution rate. The operating conditions (i.e., salinity, temperature, and mineral loading) affect the dissolution kinetics in a very complex manner because of which the observed experimental trends do not exhibit a direct trend.     

Showering in Flint, MI: Is there a DBP problem?

Lead contamination in the City of Flint, MI has been well documented over the past two years, with lead levels above the EPA Action Level until summer 2016. This resulted from an ill-fated decision to switch from Detroit water (Lake Huron) with corrosion control, to Flint River water without corrosion control. Although lead levels are now closer to normal, reports of skin rashes have sparked questions surrounding tap water in some Flint homes. This study investigated the presence of contaminants, including disinfection by-products (DBPs), in the hot tap water used for showering in the homes of residents in Flint. Extensive quantitative analysis of 61 regulated and priority unregulated DBPs was conducted in Flint hot and cold tap water, along with the analysis of 50 volatile organic compounds and a nontarget comprehensive, broadscreen analysis, to identify a possible source for the reported skin rashes. For comparison, chlorinated hot and cold waters from three other cities were also sampled, including Detroit, which also uses Lake Huron as its source water. Results showed that hot water samples generally contained elevated levels of regulated and priority unregulated DBPs compared to cold water samples, but trihalomethanes were still within regulatory limits. Overall, hot shower water from Flint was similar to waters sampled from the three other cities and did not have unusually high levels of DBPs or other organic chemicals that could be responsible for the skin rashes observed by residents. It is possible that an inorganic chemical or microbial contaminant may be responsible.     

Market basket analysis of crash data from large jurisdictions and its potential as a decision support tool

Data mining applications are becoming increasingly popular for many applications across a set of very divergent fields. Analysis of crash data is no exception. There are many data mining methodologies that have been applied to crash data in the recent past. However, one particular application conspicuously missing from the traffic safety literature until recently is association analysis or market basket analysis. The methodology is used by retailers all over the world to determine which items are purchased together. In this study, crashes are analyzed as supermarket transactions to detect interdependence among crash characteristics. The results from the analysis include simple rules that indicate which crash characteristics are associated with each other. The application is demonstrated using non-intersection crash data from the state of Florida for the year 2004. In the proposed methodology no variable needs to be assigned as dependent variable. Hence, it is useful in identifying previously unknown patterns in the data obtained from large jurisdictions (such as the State of Florida) as opposed to the data from a single roadway or intersection. Based on the association rules discovered from the analysis, it was concluded that there is a significant correlation between lack of illumination and high severity of crashes. Furthermore, it was found that under rainy conditions straight sections with vertical curves are particularly crash prone. Results are consistent with the understanding of crash characteristics and point to the potential of this methodology for the analysis of crash data collected by the state and federal agencies. The potential of this technique may be realized in the form of a decision support tool for the traffic safety administrators.