No abstract

The discovery of phytoaccumulation potential of plant species has led to its application for remediation of heavy-metal-contaminated soil and wastewater, which is termed as phytoextraction/rhizofiltration. For prediction, analysis, planning and cost-effective design of such systems, mathematical models not only are used as a screening tool but also provide optimal parameters like harvesting time, irrigation schedule, etc. Several laboratory and field scale studies have been carried out in the past, and mathematical expressions have been developed by various researchers for different phenomena like metal adsorption in soil, plant root growth with time, moisture and metal uptake by plant root, moisture movement in unsaturated zone, soil moisture relationship, etc. The complete design of any such phytoremediation program would require the knowledge of behavior of heavy-metal movement in soil, water and plant root system. In this paper, a model for simulating heavy-metal dynamics in soil, water and plant root system is developed and discussed. The governing non-linear partial differential equation is solved numerically by implicit finite difference method using Picard's iterative technique, and the formulation has been illustrated using a characteristic example. The source code is written in MATLAB.

Incomplete information is notoriously common in planning soil and groundwater remediation. For making decisions groundwater flow and transport models are commonly used. However, uncertainty in prediction arises due to imprecise information on flow and transport parameters like saturated/unsaturated hydraulic conductivity, water retention curve parameters, precipitation and evapo-transpiration rates as well as factors governing the fate of pollutant in soil like dispersion, diffusion, degradation and chemical transformation. Different methods exist for quantifying uncertainty, e.g. first and second order Taylor's Series and Monte-Carlo method. In this paper, a methodology based on fuzzy set theory is presented to express imprecision of input data, in terms of fuzzy number, to quantify the uncertainty in prediction. The application of the fuzzy set theory is demonstrated through pesticide (endosulfan) transport in an unsaturated layered soil profile. The governing partial differential equation along with fuzzy inputs, results in a non-linear optimization problem. The solution gives complete membership functions for flow (suction head) and pesticide concentration in soil column.

This study compares the ambient air particulate matter (PM10) data of 15 different coal mine environments. For most of these mine environments, the monitoring was carried out by different researchers using respirable dust sampler (RDS) that separates PM10 by centrifugal inertial separation. At two sites--Padmapur and Ghugus (Chandrapur, Maharashtra, India)--mass inertial impaction-based sampler was used for PM10 monitoring. It is observed that the spatiotemporal average value of ambient air PM10 monitored using mass inertial impactor reports relatively higher values (240-372 μg/m(3)) compared to those monitored using RDS (<227 μg/m(3)). In order to realize the severity of mine area pollution, it is compared with PM10 values found in an urban area (Delhi, India). It is found that PM10 values in Delhi (using mass inertial impactor) are much higher (300-400 μg/m(3)) than those reported for the mine environment. The data seems to indicate that the mine environment is relatively cleaner than urban air and therefore raises doubt about the appropriateness of using either mass impactor or RDS for PM10 sampling.

Exposure to PM-bound polycyclic aromatic hydrocarbons (PAHs) can elicit several types of cancer and non-cancer effects. Previous studies reported substantial burdens of PAH-induced lung cancer, but the burdens of other cancer types and non-cancer effects remain unknown. Thus, we estimate the cancer and non-cancer burden of disease, in disability-adjusted life years (DALYs), attributable to ambient PM-bound PAHs exposure in Nagpur district, India, using risk-based approach. We measured thirteen PAHs in airborne PM sampled from nine sites covering urban, peri-urban and rural areas, from February 2013 to June 2014. We converted PAHs concentrations to benzo[a]pyrene equivalence (B[a]P) for cancer and non-cancer effects using relative potency factors, and relative toxicity factors derived from quantitative structure-activity relationships, respectively. We calculated time-weighted exposure to B[a]P, averaged over 30 years, and adjusted for early-life susceptibility to cancer. We estimated the DALYs/year using B[a]P exposure levels, published toxicity data, and severity of the diseases from Global Burden of Disease 2016 database. The annual average concentration of total PM-bound PAHs was 458 ± 246 ng/m and resulted in 49,500 DALYs/year (0.011 DALYs/person/year). The PAH-related DALYs followed this order: developmental (mostly cardiovascular) impairments (55.1%) > cancer (26.5%) or lung cancer (23.1%) > immunological impairments (18.0%) > reproductive abnormalities (0.4%).