Air Pollution Control

The air we breathe is being polluted by activities such as vehicles; burning coal, oil, and other fossil fuels; and manufacturing chemicals. Air pollution can even come from smaller, everyday activities such as cooking, space heating, and degreasing and painting operations. These activities add gases and particles to the air we breathe. When these gases and particles accumulate in the air in high enough concentrations, they can harm us and our environment. The module on Air Pollution deals with the various sources of air pollution and the associated environmental and health impacts. It also discusses the appropriate measures to control/prevent the same.

Post combustion in cupola for pollution control

Carbon monoxide, a major pollutant from the cupola, is poisonous and flammable. It can vary from 12 to 25% in cupola emissions. Carbon monoxide content in cupola emissions can be reduced by the post-combustion air input at the appropriate level into the stack. Scientific support to this has been provided by simulation of the combustion process in the cupola. Location and the extent of input of air for post combustion into the stack have been determined.

Air-pollution and economics: diesel bus versus electric bus

The Bangalore Metropolitan Transport Corporation (BMTC) took an initiative to check the overall benefits of introducing electric buses as a suitable replacement for the diesel buses to tackle the burgeoning pollution in the city of Bengaluru, India. For a trial run of three months, an electric bus was procured from a Chinese company `Build Your Dreams' (BYD). Data were collected by BMTC on the operation and maintenance of the bus. This new initiative, if rightly guided, could have a direct impact on the lives of those in the city. An economic analysis of the running as well as maintenance of the electric buses within the city limits was performed. For comparison, the same analysis was performed for the data from the existing diesel bus operating on the same route. On the basis of the study, it can be concluded that the introduction of electric buses as a means of public transport in the city would be beneficial both economically as well as environmentally. The electric bus also makes much less noise, thereby helping reduce noise pollution and makes less vibration when compared to the diesel bus. This results in a more comfortable journey for the passengers.

Environmental remediation by photocatalysis

Photocatalysis refers to the oxidation and reduction reactions on semiconductor surfaces, mediated by the valence band holes and conduction band electrons, which are generated by the absorption of ultraviolet or visible light radiation. Photocatalysis is widely being practiced for the degradation and mineralization of hazardous organic compounds to CO2 and H2O, reduction of toxic metal ions to their non-toxic states, deactivation and destruction of water borne microorganisms, decomposition of air pollutants like volatile organic compounds, NOx, CO and NH3, degradation of waste plastics and green synthesis of industrially important chemicals. This review attempts to showcase the well established mechanism of photocatalysis, the use of photocatalysts for water and air pollution control,visible light responsive modified-TiO2 and non-TiO2 based materials for environmental and energy applications, and the importance of developing reaction kinetics for a comprehensive understanding and design of the processes.

River water quality response under hypothetical climate change scenarios in Tunga-Bhadra river, India

Analysis of climate change impacts on streamflow by perturbing the climate inputs has been a concern for many authors in the past few years, but there are few analyses for the impacts on water quality. To examine the impact of change in climate variables on the water quality parameters, the water quality input variables have to be perturbed. The primary input variables that can be considered for such an analysis are streamflow and water temperature, which are affected by changes in precipitation and air temperature, respectively. Using hypothetical scenarios to represent both greenhouse warming and streamflow changes, the sensitivity of the water quality parameters has been evaluated under conditions of altered river flow and river temperature in this article. Historical data analysis of hydroclimatic variables is carried out, which includes flow duration exceedance percentage (e.g. Q90), single low- flow indices (e.g. 7Q10, 30Q10) and relationships between climatic variables and surface variables. For the study region of Tunga-Bhadra river in India, low flows are found to be decreasing and water temperatures are found to be increasing. As a result, there is a reduction in dissolved oxygen (DO) levels found in recent years. Water quality responses of six hypothetical climate change scenarios were simulated by the water quality model, QUAL2K. A simple linear regression relation between air and water temperature is used to generate the scenarios for river water temperature. The results suggest that all the hypothetical climate change scenarios would cause impairment in water quality. It was found that there is a significant decrease in DO levels due to the impact of climate change on temperature and flows, even when the discharges were at safe permissible levels set by pollution control agencies (PCAs). The necessity to improve the standards of PCA and develop adaptation policies for the dischargers to account for climate change is examined through a fuzzy waste load allocation model developed earlier. Copyright (C) 2011 John Wiley & Sons, Ltd.

Fuzzy optimization model for water quality management of a river system - Closure

A fuzzy waste-load allocation model, FWLAM, is developed for water quality management of a river system using fuzzy multiple-objective optimization. An important feature of this model is its capability to incorporate the aspirations and conflicting objectives of the pollution control agency and dischargers. The vagueness associated with specifying the water quality criteria and fraction removal levels is modeled in a fuzzy framework. The goals related to the pollution control agency and dischargers are expressed as fuzzy sets. The membership functions of these fuzzy sets are considered to represent the variation of satisfaction levels of the pollution control agency and dischargers in attaining their respective goals. Two formulations—namely, the MAX-MIN and MAX-BIAS formulations—are proposed for FWLAM. The MAX-MIN formulation maximizes the minimum satisfaction level in the system. The MAX-BIAS formulation maximizes a bias measure, giving a solution that favors the dischargers. Maximization of the bias measure attempts to keep the satisfaction levels of the dischargers away from the minimum satisfaction level and that of the pollution control agency close to the minimum satisfaction level. Most of the conventional water quality management models use waste treatment cost curves that are uncertain and nonlinear. Unlike such models, FWLAM avoids the use of cost curves. Further, the model provides the flexibility for the pollution control agency and dischargers to specify their aspirations independently.

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA)problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max-min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.

Fuzzy waste load allocation model: a multiobjective approach

Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, A, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination Of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga-Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.

Proteins in Wastewater and Wastewater Sludges

Although there is some information on the total amounts of proteins in wastewater and sludges1"3 and on the amino acids in them,4-11 especially in activated sludge,12 there is almost no evidence on the nature of the proteins in these materials. A knowledge of the nature of proteins in wastewater, sludges, and similar substances would be useful not only for determining the pollutional effects on the environment and the changes in the protein structures during decomposition or treatment, but also for determining the possible usage of the resulting materials in agriculture,13 includ ing animal nutrition.

Structure of the Indian southwesterly pre-monsoon and monsoon boundary layers: Observations and numerical simulation

Characteristics of pre-monsoon and monsoon boundary layer structure and turbulence were studied in New Delhi and Bangalore, India during the summer of 1987. Micrometeorological towers were installed and instrumented at these locations to provide mean and turbulent surface layer measurements, while information on the vertical structure of the atmosphere was obtained using miniradiosondes. Thermal structures of the pre-monsoon and monsoon boundary layers were quite distinct. The daytime, pre-monsoon boundary layer observed over New Delhi was much deeper than that of the monsoon boundary layer observed over Bangalore and at times was characterized by multiple inversions. Surface, turbulent sensible heat fluxes at both sites were approximately the same (235 and 200 Wm−2 for New Delhi and Bangalore, respectively). Diurnal variations in the monsoon boundary layer at Bangalore were more regular compared to those under pre-monsoon conditions at New Delhi. One-dimensional numerical simulations of the pre-monsoon boundary layer using a turbulent energy closure scheme show good agreement with observations.

The promise of fuel cell-based automobiles

Fuel cell-based automobiles have gained attention in the last few years due to growing public concern about urban air pollution and consequent environmental problems. From an analysis of the power and energy requirements of a modern car, it is estimated that a base sustainable power of ca. 50 kW supplemented with short bursts up to 80 kW will suffice in most driving requirements. The energy demand depends greatly on driving characteristics but under normal usage is expected to be 200 Wh/km. The advantages and disadvantages of candidate fuel-cell systems and various fuels are considered together with the issue of whether the fuel should be converted directly in the fuel cell or should be reformed to hydrogen onboard the vehicle. For fuel cell vehicles to compete successfully with conventional internal-combustion engine vehicles, it appears that direct conversion fuel cells using probably hydrogen, but possibly methanol, are the only realistic contenders for road transportation applications. Among the available fuel cell technologies, polymer-electrolyte fuel cells directly fueled with hydrogen appear to be the best option for powering fuel cell vehicles as there is every prospect that these will exceed the performance of the internal-combustion engine vehicles but for their first cost. A target cost of $ 50/kW would be mandatory to make polymer-electrolyte fuel cells competitive with the internal combustion engines and can only be achieved with design changes that would substantially reduce the quantity of materials used. At present, prominent car manufacturers are deploying important research and development efforts to develop fuel cell vehicles and are projecting to start production by 2005.

Albedo enhancement over land to counteract global warming: impacts on hydrological cycle

A recent modelling study has shown that precipitation and runoff over land would increase when the reflectivity of marine clouds is increased to counter global warming. This implies that large scale albedo enhancement over land could lead to a decrease in runoff over land. In this study, we perform simulations using NCAR CAM3.1 that have implications for Solar Radiation Management geoengineering schemes that increase the albedo over land. We find that an increase in reflectivity over land that mitigates the global mean warming from a doubling of CO2 leads to a large residual warming in the southern hemisphere and cooling in the northern hemisphere since most of the land is located in northern hemisphere. Precipitation and runoff over land decrease by 13.4 and 22.3%, respectively, because of a large residual sinking motion over land triggered by albedo enhancement over land. Soil water content also declines when albedo over land is enhanced. The simulated magnitude of hydrological changes over land are much larger when compared to changes over oceans in the recent marine cloud albedo enhancement study since the radiative forcing over land needed (-8.2 W m(-2)) to counter global mean radiative forcing from a doubling of CO2 (3.3 W m(-2)) is approximately twice the forcing needed over the oceans (-4.2 W m(-2)). Our results imply that albedo enhancement over oceans produce climates closer to the unperturbed climate state than do albedo changes on land when the consequences on land hydrology are considered. Our study also has important implications for any intentional or unintentional large scale changes in land surface albedo such as deforestation/afforestation/reforestation, air pollution, and desert and urban albedo modification.

Multicomponent Assembly of Fluorescent-Tag Functionalized Ligands in Metal-Organic Frameworks for Sensing Explosives

Detection of trace amounts of explosive materials is significantly important for security concerns and pollution control. Four multicomponent metal organic frameworks (MOFs-12, 13, 23, and 123) have been synthesized by employing ligands embedded with fluorescent tags. The multicomponent assembly of the ligands was utilized to acquire a diverse electronic behavior of the MOFs and the fluorescent tags were strategically chosen to enhance the electron density in the MOFs. The phase purity of the MOFs was established by PXRD, NMR spectroscopy, and finally by singlecrystal XRD. Single-crystal structures of the MOFs-12 and 13 showed the formation of three-dimensional porous networks with the aromatic tags projecting inwardly into the pores. These electron-rich MOFs were utilized for detection of ex- plosive nitroaromatic compounds (NACs) through fluorescence quenching with high selectivity and sensitivity. The rate of fluorescence quenching for all the MOFs follows the order of electron deficiency of the NACs. We also showed the detection of picric acid (PA) by luminescent MOFs is not always reliable and can be misleading. This attracts our attention to explore these MOFs for sensing picryl chloride (PC), which is as explosive as picric acid and used widely to prepare more stable explosives like 2,4,6-trinitroaniline from PA. Moreover, the recyclability and sensitivity studies indicated that these MOFs can be reused several times with parts per billion (ppb) levels of sensitivity towards PC and 2,4,6-trinitrotoluene (TNT).