Sampling over time: developing a cost effective and precise exposure assessment program

Studies requiring ambient exposure assessments invariably ask: How often should measurements be taken? Answer to such questions is dictated by budgetary considerations as well as spatial and temporal variability in the data. For example, do we obtain measurements during all seasons, all months within seasons, weeks within months and days within weeks? On one hand, we can obtain a one-time snapshot sample and regard it as representing the "true" mean exposure. On the other hand, we may obtain a large number of measurements over time and then average these in order to represent this "true" mean exposure. The former estimate is the least expensive but may also be the least precise while the latter, may be very precise but prohibitively costly. In this paper, we demonstrate how a pilot study can be undertaken with a potentially promising and feasible sampling plan for the full-scale study. By applying the statistical methodology of variance component analysis (VCA) to the pilot study data and exploiting mathematical relationship between the variance of the overall mean exposure and posited variance components, we can develop a sampling design with decreased sampling costs and/or increased precision of the mean exposure. Our approach was applied to determine sampling design choices for an on-going study that aimed at assessing ambient particulate matter exposure. We conclude that a pilot study followed by the VCA analysis may often lead to sampling design choices that offer considerable cost savings and, at the same time, promise to provide relatively precise estimates of the mean exposure for the subsequent full-scale study.     

Agricultural GHG emission and calorie intake nexus among different socioeconomic households of rural eastern India

A study was conducted to examine the interrelationships among socioeconomic factors, household consumption patterns, calorie intake and greenhouse gas emissions factors in rural eastern India based on household survey data. Findings indicated that higher monthly per capita incomes (12.1–80.1$) were associated with greater average calorie intakes (2021–2525 kcal d^?1). As estimated by the FEEDME model, in total 17.2% of the population was calorie malnourished with a regional disparity of 29.4–18.2% malnourishment. Greenhouse gas (GHG) emissions were calculated only on the basis of crop and livestock production and consumption. Rice accounted for the highest share of total GHG emissions, on average 82.6% on a production basis, which varied from 58.1% to 94.9% in regional basis. Rice contributed the greatest share (~?65% and 66.2%) in terms of both calories and GHG emissions (CO₂ eq y^?1), respectively, on a consumption basis. We conclude that extensive rice farming and increasing animal product consumption are dominant factors in the higher carbon footprint in this region and are likely to further increase with increase in per capita income. This study provides useful information to help for better crop planning and for fine-tuning food access policy, to reduce carbon footprint and calorie malnutrition.

     

Kelp as a Bioindicator: Does it Matter Which Part of 5 M Long Plant is Used for Metal Analysis?

Kelp may be useful as a bioindicator because they are primary producers that are eaten by higher trophic level organisms, including people and livestock. Often when kelp or other algae species are used as bioindicators, the whole organism is homogenized. However, some kelp can be over 25 m long from their holdfast to the tip of the blade, making it important to understand how contaminant levels vary throughout the plant. We compared the levels of arsenic, cadmium, chromium, lead, manganese, mercury and selenium in five different parts of the kelp Alaria nana to examine the variability of metal distribution. To be useful as a bioindicator, it is critical to know whether levels are constant throughout the kelp, or which part is the highest accumulator. Kelp were collected on Adak Island in the Aleutian Chain of Alaska from the Adak Harbor and Clam Cove, which opens onto the Bering Sea. In addition to determining if the levels differ in different parts of the kelp, we wanted to determine whether there were locational or size-related differences. Regression models indicated that between 14% and 43% of the variation in the levels of arsenic, cadmium, chromium, manganese, mercury, and selenium was explained by total length, part of the plant, and location (but not for lead). The main contributors to variability were length (for arsenic and selenium), location (mercury), and part of the plant (for arsenic, cadmium, chromium and manganese). The higher levels of selenium occurred at Clam Cove, while mercury was higher at the harbor. Where there was a significant difference among parts, the holdfast had the highest levels, although the differences were not great. These data indicate that consistency should be applied in selecting the part of kelp (and the length) to be used as a bioindicator. While any part of Alaria could be collected for some metals, for arsenic, cadmium, chromium, and manganese a conversion should be made among parts. In the Aleutians the holdfast can be perennial while the blade, whipped to pieces by winter wave action, is regrown each year. Thus the holdfast may be used for longer-term exposure for arsenic, cadmium, chromium and manganese, while the blade can be used for short-term exposure for all metals. Cadmium, lead and selenium were at levels that suggest that predators, including people, may be at risk from consuming Alaria. More attention should be devoted to heavy metal levels in kelp and other algae from Adak, particularly where they may play a role in a subsistence diets.     

Physical characterization,magnetic measurements,REE geochemistry and biomonitoring of dust load accumulated during a protracted winter fog period and their implications

The winter fog in India is a recurrent phenomenon for more than a decade now affecting the entire Himalayan and sub-Himalayan regions covering an area of nearly 500,000 km². Every winter (December–January), the air and surface transports in cities of northern India (Amritsar, New Delhi, Agra, Gwalior, Kanpur, Lucknow, and Allahabad) are severely disrupted with visibility reduced to <50 m at times. Since dust particles are known to act as nuclei for the fog formation, this study is aimed to carry out physicochemical characterization of the dust particulates accumulated during a protracted fog period from one of the severely fog affected cities of north India (Allahabad; 25°27′33.40″N–81°52′45.47″E). The dust-loaded tree leaves belonging to Ficus bengalensis and Ficus religiosa from 50 different locations between January 24 and 31, 2010 are sampled and characterized. The mass of dust, color, grain shape, size, phase constituents, and mineral magnetic parameters, such as magnetic susceptibility, SIRM, χ _fd%, and S-ratio, show minor variation and the regional influence outweighs local anthropogenic contributions. The dust compositions show fractionated rare earth element pattern with a pronounced negative Eu anomaly similar to upper continental crust and further suggesting their derivation from sources located in parts of north and central India.     

Modelling the Removal of Gaseous Pollutants and Particulate Matters from the Atmosphere of a City by Rain: Effect of Cloud Density

In this paper, an original nonlinear mathematical model for the removal of gaseous pollutants and particulate matters from the atmosphere of an industrial city by rain is proposed and analyzed. It is assumed that five interacting phases in the atmosphere of the city exist, i.e., cloud droplets phase, raindrops phase, gaseous pollutants phase, particulate matters phase, and the phase of absorbed gaseous pollutants in raindrops. It is assumed further that these phases undergo nonlinear interactions in the atmosphere, while gaseous pollutant interacts with cloud droplets as well as with raindrops but particulate matters interact only with raindrops. The gravitational settling and reversible reaction processes have also been considered appropriately in the model. By analyzing the model, it is shown that both the gaseous pollutants and particulate matters may be removed from the atmosphere under certain conditions, provided the rates of formation of cloud droplets and raindrops are sufficiently large. It is noted that under unfavorable atmospheric conditions, rain does not occur and pollutants are not removed from the atmosphere.     

Autoclave and pulsed ultrasound cavitation based thermal activation of persulfate for regeneration of hydrogen titanate nanotubes as recyclable dye adsorbent

Environmental Science and Pollution Research - In the dye removal application, regeneration of hydrogen titanate nanotubes (HTN, H2Ti3O7) has been achieved via thermal activation of persulfate...     

Heat loss analysis: An approach toward the revival of parabolic dish type solar cooker

Present work investigates a noble approach toward the heat loss analysis of parabolic dish type solar cooker. Various experiments have been done on cooking pot to get the input parameter for calculation purposes. Cooking pot was kept at the focus of a parabolic dish type concentrator and repeated experiments have been done to measure solar radiation intensity (direct and Indirect) using a pyrometer, temperature at the focus of parabolic dish using a thermocouple and air velocity using hot wire anemometer to investigate the heat losses from the cooking pot. In the present article, a numerical approach has been performed to define the new parameter called performance index of the cooking pot which decides how the useful energy of working fluid inside the cooking pot approaches concentration ratio of the parabolic dish type solar cooker. The present analysis shows that the performance index varies from 15.45 to 17.66 and efficiency varies from 85.83% to 98.10% with the time of the day.