Emission of isoprene from common Indian plant species and its implications for regional air quality

Isoprene is most dominant volatile organic compounds (VOC) emitted by many plants. In this study 40 common Indian plant species were examined for isoprene emission using dynamic flow through enclosure chamber technique. Isoprene emission rates of plants species were found to vary from undetectable to 69.5 microg g(-1) h(-1) (Madhuca latifolia). Besides, an attempt has been made to evaluate suitability of 80 common Indian plant species for planting programmes. Out of 80 species, 29 species were moderate to high emitters (10 to < or =25 microg g(-1) h(-1)), 12 species were low emitter emitters (1 to < or =10 microg g(-1) h(-1)) and remaining 39 species were found to be negligible or non emitters (<1 microg g(-1) h(-1)) of isoprene. About 50% plant species selected for planting programmes in India were found to be moderate to high emitters of isoprene.     

Potential effects on the marine environment of dredging of the Bonny channel in the Niger Delta

This study is an assessment of the possible effects of the dredging project on the water quality of the surrounding environment. Water quality data for the Bonny offshore river were collected. The parameters assessed were temperature, dissolved oxygen (DO), pH, biochemical oxygen demand (BOD), total dissolved solids (TDS), total suspended solids (TSS), nitrogen as nitrate, and phosphate. The concentrations of TDS, TSS, and nitrate far exceeded the permissible standard. There were significant differences between the dry and rainy season values of BOD5, TDS, TSS, nitrate, and phosphate. Also, the sediment physicochemical analysis indicated the presence of heavy metals such as Pb, Fe, Cd, Zn, Cr, and elements such as Ca, K, and Na. Following an assessment of the potential impact of the project using interaction matrix and checklist questionnaires, results showed that the major physicochemical parameters influenced by dredging are DO, TDS, TSS, heavy metals and calcium, potassium, and sodium. Mitigation measures for eliminating or reducing the negative impacts of dredging are presented.     

Study of electromagnetic radiation pollution in an Indian city

Electromagnetic radiation emitted by cell phone towers is a form of environmental pollution and is a new health hazard, especially to children and patients. The present studies were taken to estimate the microwave/RF pollution by measuring radiation power densities near schools and hospitals of Chandigarh city in India. The cell phone radiations were measured using a handheld portable power density meter TES 593 and specific absorption rates were estimated from the measured values. These values of electromagnetic radiation in the environment were compared with the levels at which biological system of humans and animals starts getting affected. The values were also compared with the international exposure limits set by the International Commission on Non-Ionizing Radiation Protection (ICNIRP). The highest measured power density was 11.48?mW/m(2) which is 1,148% of the biological limit. The results indicated that the exposure levels in the city were below the ICNIRP limit, but much above the biological limit.     

Adsorption–desorption of metolachlor and atrazine in Indian soils: effect of fly ash amendment

The effect of two fly ashes as soil amendment on the adsorption–desorption of metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylphenyl)] and atrazine (2-chloro-4-ethylamino-6-isopropylamino-1,3,5-triazine) was studied in alluvial and laterite soils. The adsorption data for both the herbicides fitted well the Freundlich equation, and Freundlich adsorption coefficient (K _f) increased with an increase of fly ash amount. Both the fly ashes differed in their extent to increase herbicide sorption, and the effect was different in different soils. Atrazine was sorbed more in the soils/soils?+?fly ash mixtures than the metolachlor. The K _f values showed significant correlation with the amount of fly ash amendment (correlation coefficient, R?>?0.982). The desorption isotherms also fitted the Freundlich equation, and desorption showed hysteresis which increased with an increase in the content of fly ash amendment. The free energy change (ΔG) indicated that the sorption process is exothermic, spontaneous, and physical in nature. The study has shown that fly ash as soil amendment significantly increased the sorption of metolachlor and atrazine, but the effect is soil- and fly ash-specific.     

Assessment and monitoring of long-term forest cover changes in Odisha, India using remote sensing and GIS

Deforestation and fragmentation are important concerns in managing and conserving tropical forests and have global significance. In the Indian context, in the last one century, the forests have undergone significant changes due to several policies undertaken by government as well as increased population pressure. The present study has brought out spatiotemporal changes in forest cover and variation in forest type in the state of Odisha (Orissa), India, during the last 75 years period. The mapping for the period of 1924–1935, 1975, 1985, 1995 and 2010 indicates that the forest cover accounts for 81,785.6 km² (52.5 %), 56,661.1 km² (36.4 %), 51,642.3 km² (33.2 %), 49,773 km² (32 %) and 48,669.4 km² (31.3 %) of the study area, respectively. The study found the net forest cover decline as 40.5 % of the total forest and mean annual rate of deforestation as 0.69 %?year^?1 during 1935 to 2010. There is a decline in annual rate of deforestation during 1995 to 2010 which was estimated as 0.15 %. Forest type-wise quantitative loss of forest cover reveals large scale deforestation of dry deciduous forests. The landscape analysis shows that the number of forest patches (per 1,000) are 2.463 in 1935, 10.390 in 1975, 11.899 in 1985, 12.193 in 1995 and 15.102 in 2010, which indicates high anthropogenic pressure on the forests. The mean patch size (km²) of forest decreased from 33.2 in 1935 to 5.5 in 1975 and reached to 3.2 by 2010. The study demonstrated that monitoring of long term forest changes, quantitative loss of forest types and landscape metrics provides critical inputs for management of forest resources.     

Multivariate analysis of potentially toxic metals in sediments of a tropical coastal lagoon

Surface sediments collected from the Lagos Lagoon, Nigeria, and three adjoining rivers were analysed for their physicochemical properties and pseudo-total concentration of the potentially toxic metals (PTM) Cd, Cr, Cu, Pb and Zn. The concentration of the PTM varied seasonally and spatially. Odo-Iyaalaro was observed to be the most polluted river, with highest concentrations of 42.1 mg kg^?1, 102 mg kg^?1, 185 mg kg^?1, 154 mg kg^?1 and 1040 mg kg^?1 of Cd, Cr, Cu, Pb and Zn, respectively, while Ibeshe River was the least contaminated, apart from a site affected by Cu from the textile industry. Some of the sediments were found to be above the consensus-based probable effect concentrations and Dutch sediment guideline for metals. Overall metal concentrations were similar to those reported for other tropical lagoon and estuarine systems affected by anthropogenic inputs as a result of rapid urbanisation. Due to the large number of samples, principal component analysis was used to examine relationships within the data set. Generally, sediments collected during the dry season were observed to have higher concentration of PTM than those collected during the rainy season. This means that PTM could accumulate over a prolonged period and then be released relatively rapidly, on an annual basis, into tropical lagoon systems.     

Receptor model-based source apportionment of particulate pollution in Hyderabad, India

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2?±?24.6, 96.2?±?12.1, and 64.3?±?21.2 μg/m³ of PM₁₀, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m³. In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM₁₀ and PM_2.5 size fractions for three seasons. The receptor modeling results indicated that the PM₁₀ pollution is dominated by the direct vehicular exhaust and road dust (more than 60 %). PM_2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.     

Prediction of the solubility of zinc, copper, nickel, cadmium, and lead in metal-contaminated soils

Risk assessment of metal-contaminated soil depends on how precisely one can predict the solubility of metals in soils. Responses of plants and soil organisms to metal toxicity are explained by the variation in free metal ion activity in soil pore water. This study was undertaken to predict the free ion activity of Zn, Cu, Ni, Cd, and Pb in metal-contaminated soil as a function of pH, soil organic carbon, and extractable metal content. For this purpose, 21 surface soil samples (0–15 cm) were collected from agricultural lands of various locations receiving sewage sludge and industrial effluents for a long period. One soil sample was also collected from agricultural land which has been under intensive cropping and receiving irrigation through tube well water. Soil samples were varied widely in respect of physicochemical properties including metal content. Total Zn, Cu, Ni, Cd, and Pb in experimental soils were 2,015?±?3,373, 236?±?286, 103?±?192, 29.8?±?6.04, and 141?±?270 mg kg^?1, respectively. Free metal ion activity, viz., pZn²⁺, pCu²⁺, pNi²⁺, pCd²⁺, and pPb²⁺, as estimated by the Baker soil test was 9.37?±?1.89, 13.1?±?1.96, 12.8?±?1.89, 11.9?±?2.00, and 11.6?±?1.52, respectively. Free metal ion activity was predicted by pH-dependent Freundlich equation (solubility model) as a function of pH, organic carbon, and extractable metal. Results indicate that solubility model as a function of pH, Walkley–Black carbon (WBC), and ethylenediaminetetraacetic acid (EDTA)-extractable metals could explain the variation in pZn²⁺, pCu²⁺, pNi²⁺, pCd²⁺, and pPb²⁺ to the extent of 59, 56, 46, 52, and 51 %, respectively. Predictability of the solubility model based on pH, KMnO₄-oxidizable carbon, and diethylenetriaminepentaacetic acid-extractable or CaCl₂-extractable metal was inferior compared to that based on EDTA-extractable metals and WBC.     

Simultaneous analysis of endosulfan, chlorpyrifos, and their metabolites in natural soil and water samples using gas chromatography-tandem mass spectrometry

Analysis of endosulfan, chlorpyrifos, and their nonpolar metabolites in extracts from environmental aqueous and soil samples was performed using a gas chromatography-tandem mass spectrometry (GC–MS/MS) technique. Full-scan GC–MS analysis showed poor sensitivity for some of the metabolites (endodiol and endosulfan ether). A multisegment MS/MS method was developed and MS/MS parameter isolation time, excitation time, excitation voltage, and maximum excitation energy were optimized for chosen precursor ions to enhance selectivity and sensitivity of the analysis. The use of MS/MS with optimized parameters quantified analytes with significantly higher accuracy, and detection limits were lowered to ~1/6th compared with the full-scan method. Co-eluting compounds, chlorpyrifos and chlorpyrifos oxon, were also analyzed successfully in the MS/MS mode by choosing exclusive precursor ions. Analysis of soil and water phase samples from contaminated soil slurry bioreactors showed that the MS/MS method could provide more reliable estimates of these pesticide and metabolites (especially those present in low concentrations) by annulling interferences from soil organic matter.     

Source identification and apportionment of PM2.5 and PM2.5−10 in iron and steel scrap smelting factory environment using PMF,PCFA and UNMIX receptor models

To identify the potential sources responsible for the particulate matter emission from secondary iron and steel smelting factory environment, PM_2.5 and PM_2.5?10 particles were collected using the low-volume air samplers twice a week for a year. The samples were analyzed for the elemental and black carbon content using x-ray fluorescence spectrometer and optical transmissometer, respectively. The average mass concentrations were 216.26, 151.68, and 138. 62 μg/m³ for PM_2.5 and 331.36, 190.01, and 184.60 μg/m³ for PM_2.5?10 for the production, outside M1 and outside M2 sites, respectively. The same size resolved data set were used as input for the positive matrix factorization (PMF), principal component factor analysis (PCFA), and Unmix (UNMIX) receptor modeling in order to identify the possible sources of particulate matter and their contribution. The PMF resolved four sources with their respective contributions were metal processing (33 %), e-waste (33 %), diesel emission (22 %) and soil (12 %) for PM_2.5, and coking (50 %), soil (29 %), metal processing (16 %) and diesel combustion (5 %) for PM_2.5?10. PCFA identified soil, metal processing, Pb source, and diesel combustion contributing 45, 41, 9, and 5 %, respectively to PM_2.5 while metal processing, soil, coal combustion and open burning contributed 43, 38, 12, and 7 %, respectively to the PM_2.5?10. Also, UNMIX identified metal processing, soil, and diesel emission with 43, 42 and 15 % contributions, respectively for the fine fraction, and metal processing (71 %), soil (21 %) and unidentified source (1 %) for the coarse fraction. The study concluded that metal processing and e-waste are the major sources contributing to the fine fraction while coking and soil contributed to the coarse fraction within the factory environment. The application of PMF, PCFA and UNMIX receptor models improved the source identification and apportionment of particulate matter drive in the study area.