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.     

The Role of Abatement Costs in GHG Permit Allocations: A Global Stabilization Scenario Analysis

Our objective is to propose permit allocation schemes that lead to a fair distribution of the net abatement cost among regions in a global greenhouse gas (GHG) stabilization scenario. We use a detailed technology-based energy model, World-MARKAL, to determine efficient abatement decisions, and to calculate the regional gross abatement costs (before permit allocation and trading). The net abatement costs are then calculated and used for different permit allocation schemes.     

Design and evaluation of an inlet conditioner to dry particles for real-time particle sizers

Real-time particle sizers provide rapid information about atmospheric particles, particularly peak exposures, which may be important in the development of adverse health outcomes. However, these instruments are subject to erroneous readings in high-humidity environments when compared with measurements from filter-based, federal reference method (FRM) samplers. Laboratory tests were conducted to evaluate the ability of three inlet conditioners to dry aerosol prior to entering a real-time particle sizer for measuring coarse aerosols (Model 3321 Aerodynamic Particle Sizer, APS) under simulated highly humid conditions. Two 30 day field studies in Birmingham, AL, USA were conducted to compare the response of two APSs operated with and without an inlet conditioner to that measured with FRM samplers. In field studies, the correlation of PM(10-2.5) derived from the APS and that measured with the FRM was substantially stronger with an inlet conditioner applied (r2 ranged from 0.91 to 0.99) than with no conditioner (r2 = 0.61). Laboratory experiments confirmed the ability of the heater and desiccant conditioner to remove particle-borne moisture. In field tests, water was found associated with particles across the sizing range of the APS (0.5 microm to 20 microm) when relative humidity was high in Birmingham. Certain types of inlet conditioners may substantially improve the correlation between particulate mass concentration derived from real-time particle sizers and filter-based samplers in humid conditions.     

Optimal Expansion Strategy for a Sewer System under Uncertainty

Because of fast urban sprawl, land use competition, and the gap in available funds and needed funds, municipal decision makers and planners are looking for more cost-effective and sustainable ways to improve their sewer infrastructure systems. The dominant approaches have turned to planning the sanitary sewer systems within a regional context, while the decentralized and on-site/cluster wastewater systems have not overcome the application barriers. But regionalization policy confers uncertainties and risks upon cities while planning for future events. Following the philosophy of smart growth, this paper presents several optimal expansion schemes for a fast-growing city in the US/Mexico borderlands—the city of Pharr in Texas under uncertainty. The waste stream generated in Pharr is divided into three distinct sewer sheds within the city limit, including south region, central region, and north region. The options available include routing the wastewater to a neighboring municipality (i.e., McAllen) for treatment and reuse, expanding the existing wastewater treatment plant (WWTP) in the south sewer shed, and constructing a new WWTP in the north sewer shed. Traditional deterministic least-cost optimization applied in the first stage can provide a cost-effective and technology-based decision without respect to associated uncertainties system wide. As the model is primarily driven by the fees charged for wastewater transfer, sensitivity analysis was emphasized by the inclusion of varying flat-rate fees for adjustable transfer schemes before contracting process that may support the assessment of fiscal benefits to all parties involved. Yet uncertainties might arise from wastewater generation, wastewater reuse, and cost increase in constructing and operating the new wastewater treatment plant simultaneously. When dealing with multiple sources of uncertainty, the grey mixed integer programming (GIP) model, formulated in the second stage, can further allow all sources of uncertainties to propagate throughout the optimization context, simultaneously leading to determine a wealth of optimal decisions within a reasonable range. Both models ran for three 5-year periods beginning in 2005 and ending in 2020. The dynamic outputs of this analysis reflect the systematic concerns about integrative uncertainties within this decision analysis, which enable decision makers and stakeholders to make all-inclusive decisions for sanitary sewer system expansion in an economically growing region.     

Modelling Tracer Dispersion from Landfills

Several wind tunnel experiments of tracer dispersion from reduced-scale landfill models are presented in this paper. Different experimental set-ups, hot-wire anemometry, particle image velocimetry and tracer concentration measurements were used for the characterisation of flow and dispersion phenomena nearby the models. The main aim of these experiments is to build an extensive experimental data set useful for model validation purposes. To demonstrate the potentiality of the experimental data set, a validation exercise on several mathematical models was performed by means of a statistical technique. The experiments highlighted an increase in pollutant ground level concentrations immediately downwind from the landfill because of induced turbulence and mean flow deflection. This phenomenon turns out to be predominant for the dispersion process. Tests with a different set-up showed an important dependence of the dispersion phenomena from the landfill height and highlighted how complex orographic conditions downwind of the landfill do not affect significantly the dispersion behaviour. Validation exercises were useful for model calibration, improving code reliability, as well as evaluating performances. The Van Ulden model proved to give the most encouraging results.     

A Model for Landscape Planning Under Complex Spatial Conditions

We present a new mathematical programming framework that is adaptable to a variety of spatially explicit landscape problems in environmental investment, conservation, and land-use planning, transport planning, and agriculture. As part of capturing spatial interdependencies, the framework considers decision variables at two levels, finely spaced grid cells and landholdings. We applied the framework to an environmental investment problem using objective functions representing biodiversity and carbon sequestration. We also tested the model to optimize the path of a road through part of the landscape. Using the Nambucca case study in eastern Australia, we applied a hybrid greedy randomised adaptive search procedure (GRASP) to find solutions to the model.     

Extension of the EUROS Integrated Air Quality Model to Fine Particulate Matter by Coupling to CACM/MADRID 2

The European Operational Smog (EUROS) integrated air quality modelling system has been extended to model fine particulate matter (PM). From an extended literature study, the Caltech Atmospheric Chemistry Mechanism and the Model of Aerosol Dynamics, Reaction, Ionisation and Dissolution were selected and recently coupled to EUROS. Currently, modelling of mass and chemical composition of aerosols in two size fractions (PM_2.5 and PM_10–2.5) is possible. The chemical composition is expressed in terms of seven components: ammonium, nitrate, sulphate, elementary carbon, primary inorganic compounds, primary organic compounds and secondary organic compounds. Calculated PM₁₀ concentrations and chemical composition are presented for two summer months of the year 2003 (1 July to 31 August).     

Development and Parameterization of a Rain- and Fire-driven Model for Exploring Elephant Effects in African Savannas

We describe the development and parameterization of a grid-based model of African savanna vegetation processes. The model was developed with the objective of exploring elephant effects on the diversity of savanna species and structure, and in this formulation concentrates on the relative cover of grass and woody plants, the vertical structure of the woody plant community, and the distribution of these over space. Grid cells are linked by seed dispersal and fire, and environmental variability is included in the form of stochastic rainfall and fire events. The model was parameterized from an extensive review of the African savanna literature; when available, parameter values varied widely. The most plausible set of parameters produced long-term coexistence between woody plants and grass, with the tree–grass balance being more sensitive to changes in parameters influencing demographic processes and drought incidence and response, while less sensitive to fire regime. There was considerable diversity in the woody structure of savanna systems within the range of uncertainty in tree growth rate parameters. Thus, given the paucity of height growth data regarding woody plant species in southern African savannas, managers of natural areas should be cognizant of different tree species growth and damage response attributes when considering whether to act on perceived elephant threats to vegetation.     

Development of tiger habitat suitability model using geospatial tools—a case study in Achankmar Wildlife Sanctuary (AMWLS), Chhattisgarh India

Geospatial tools supported by ancillary geo-database and extensive fieldwork regarding the distribution of tiger and its prey in Anchankmar Wildlife Sanctuary (AMWLS) were used to build a tiger habitat suitability model. This consists of a quantitative geographical information system (GIS) based approach using field parameters and spatial thematic information. The estimates of tiger sightings, its prey sighting and predicted distribution with the assistance of contextual environmental data including terrain, road network, settlement and drainage surfaces were used to develop the model. Eight variables in the dataset viz., forest cover type, forest cover density, slope, aspect, altitude, and distance from road, settlement and drainage were seen as suitable proxies and were used as independent variables in the analysis. Principal component analysis and binomial multiple logistic regression were used for statistical treatments of collected habitat parameters from field and independent variables respectively. The assessment showed a strong expert agreement between the predicted and observed suitable areas. A combination of the generated information and published literature was also used while building a habitat suitability map for the tiger. The modeling approach has taken the habitat preference parameters of the tiger and potential distribution of prey species into account. For assessing the potential distribution of prey species, independent suitability models were developed and validated with the ground truth. It is envisaged that inclusion of the prey distribution probability strengthens the model when a key species is under question. The results of the analysis indicate that tiger occur throughout the sanctuary. The results have been found to be an important input as baseline information for population modeling and natural resource management in the wildlife sanctuary. The development and application of similar models can help in better management of the protected areas of national interest.     

Seasonal air quality profile of inorganic ionic composition of PM10 near Taj Mahal in Agra, India

Atmospheric aerosols and their impacts on the environment particularly on human health is an issue of significant public and governmental concern. Though studies on air quality related to total suspended particulate matter have done by various authors in India, yet respirable suspended particulate matter (PM₁₀) is not characterized so far particularly in a historical and world heritage city like Agra. This study presents seasonal variation in mass levels of PM₁₀ and its ionic composition. PM₁₀ samples were collected in the proximity of Taj Mahal and subjected to chemical analysis using ion chromatography technique. The preliminary findings reveal that the 24-h average of PM₁₀ mass level varies from 115 to 233, 155 to 321, and 33 to 178 μg/m³, respectively, in summer, winter, and rainy seasons indicating critical pollution situation. These values are very much higher than the National Ambient Air Quality Standards of 75 μg/m³ (prescribed by Central Pollution Control Board, India) in both of summer and winter seasons whereas quite near the permissible limits in rainy season. The equivalent ratios of NH₄ ⁺ to nonsea salt SO₄ ^2? and NO₃ ^? and ∑Cations to ∑Anios were found to be greater than unity indicating high source strength of ammonia and alkaline nature of aerosols. The study suggests the need for continuous and long-term systematical sampling and detailed physiochemical analysis of PM₁₀ and also to know the characteristics of PM in background areas for better understanding of the emission sources.