Development of the hybrid cells in series model to simulate ammonia nutrient pollutant transport along the Umgeni River

Discharge of organic waste results in high nutrient pollution of the water bodies which is a major menace to the environment. A high quantity of nutrients such as ammonia causes a reduction in the dissolved oxygen level and induces algal growth in the water bodies. Water quality models have been the tools to evaluate the rate at which streams can disperse the pollutants they receive. Many water quality models are flawed either because of their inadequacy to completely simulate the advection component of the pollutant transport, or because of the limited application of the models, due to inaccurate estimation of model parameters. The hybrid cell in series (HCIS) developed by Ghosh et al. (2004) has been able to overcome such difficulties associated with the mixing cell-based models. Thus, the current study focuses on developing an analytical solution for the pollutant transport of the ammonia concentration through the plug flow, the first and second well-mixed cells of the HCIS model. The HCIS model coupled with the first order kinetic equation for ammonia nutrient was developed to simulate the ammonia pollutant concentration in the water column. The ammonia concentration at various points along the river system was assessed by considering the effects of the transformation of ammonia to nitrite, the uptake of ammonia by the algae, the respiration rate of the algae and the input of benthic source to the ammonia concentration in the water column. The proposed model was tested using synthetic data, and the HCIS-NH₃ model simulations for spatial and temporal variation of ammonia pollutant transport were analysed. The simulated results of the HCIS-NH₃ model agreed with the Fickian-based advection-dispersion equation (ADE) for simulating ammonia concentration solved using an explicit finite difference scheme. The HCIS-NH₃ model also showed a good agreement with the observed data from the Umgeni River, except during rainy periods.     

Sustainable cooking energy options for rural poor people in India: an empirical study

Currently, energy consumption for cooking in rural households of India is mostly based on fuelwood used in traditional stoves. This paper presents results of a study carried out in a forest fringe area of India on cooking energy use. The concept of calculating levelized cost as cost per unit of useful energy is applied on source–device combinations of cooking and validated in Bargaon Community Development Block of Sundergarh District in Odisha, India. About 92 % of the households in the study area use fuelwood as the only energy source for cooking; the total use of fuelwood for only cooking, in the Block is nearly 1.8 times the total sustainable wood supply showing an urgent need for promoting alternative cooking energy options. This paper also presents an assessment of different cooking options in terms of cost per unit of useful cooking energy. LPG, biogas and gasifier stoves are found to be far too expensive for the local people. Briquette-fired improved stoves appear to be a promising cooking energy option in the study area. Government support and intervention are recommended for promoting this option.     

Measured carbon monoxide concentrations from stock and reduced-emission prototype portable generators operated in an attached garage

There is concern about the hazard of acute residential CO exposures from portable gasoline-powered generators, which can result in death or serious adverse health effects in exposed individuals. To address this hazard, the U.S. Consumer Product Safety Commission has developed low CO emission prototype generators by adapting off-the-shelf emission control technologies onto commercially available generators. A series of tests was conducted to characterize the indoor CO concentrations resulting from portable generators operating in the attached garage of a research house under seven different test house/garage configurations. The tested generators include both unmodified and modified low CO emission prototypes. It was found that CO concentrations varied widely, with peak house CO concentrations ranging from under 10 ppm to over 10,000 ppm. The highest concentrations in the house resulted from operation of the unmodified generator in the garage with the garage bay door closed and the house access door open. The lowest concentrations resulted from operation of a modified low CO emission prototype in the garage with the garage bay door open and the house access door closed. These tests documented reductions of up to 98% in CO concentrations due to emissions from two low CO emission portable generators compared to a stock generator.

Implications: Improper portable generator use has caused 800 U.S. deaths in the past 14 years. Generators operated in attached garages can cause CO to quickly reach deadly levels. Two low-emission prototypes generators were tested and had CO emissions reduced by up to 98%. Low-emission generators can reduce the risk of consumer poisonings and deaths.     

Overview of surface measurements and spatial characterization of submicrometer particulate matter during the DISCOVER-AQ 2013 campaign in Houston,TX

The sources of submicrometer particulate matter (PM₁) remain poorly characterized in the industrialized city of Houston, TX. A mobile sampling approach was used to characterize PM₁ composition and concentration across Houston based on high-time-resolution measurements of nonrefractory PM₁ and trace gases during the DISCOVER-AQ Texas 2013 campaign. Two pollution zones with marked differences in PM₁ levels, character, and dynamics were established based on cluster analysis of organic aerosol mass loadings sampled at 16 sites. The highest PM₁ mass concentrations (average 11.6 ± 5.7 µg/m³) were observed to the northwest of Houston (zone 1), dominated by secondary organic aerosol (SOA) mass likely driven by nighttime biogenic organonitrate formation. Zone 2, an industrial/urban area south/east of Houston, exhibited lower concentrations of PM₁ (average 4.4 ± 3.3 µg/m³), significant organic aerosol (OA) aging, and evidence of primary sulfate emissions. Diurnal patterns and backward-trajectory analyses enable the classification of airmass clusters characterized by distinct PM sources: biogenic SOA, photochemical aged SOA, and primary sulfate emissions from the Houston Ship Channel. Principal component analysis (PCA) indicates that secondary biogenic organonitrates primarily related with monoterpenes are predominant in zone 1 (accounting for 34% of the variability in the data set). The relevance of photochemical processes and industrial and traffic emission sources in zone 2 also is highlighted by PCA, which identifies three factors related with these processes/sources (~50% of the aerosol/trace gas concentration variability). PCA reveals a relatively minor contribution of isoprene to SOA formation in zone 1 and the absence of isoprene-derived aerosol in zone 2. The relevance of industrial amine emissions and the likely contribution of chloride-displaced sea salt aerosol to the observed variability in pollution levels in zone 2 also are captured by PCA.

Implications: This article describes an urban-scale mobile study to characterize spatial variations in submicrometer particulate matter (PM₁) in greater Houston. The data set indicates substantial spatial variations in PM₁ sources/chemistry and elucidates the importance of photochemistry and nighttime oxidant chemistry in producing secondary PM₁. These results emphasize the potential benefits of effective control strategies throughout the region, not only to reduce primary emissions of PM₁ from automobiles and industry but also to reduce the emissions of important secondary PM₁ precursors, including sulfur oxides, nitrogen oxides, ammonia, and volatile organic compounds. Such efforts also could aid in efforts to reduce mixing ratios of ozone.     

Urban heat island (UHI) influence on secondary pollutant formation in a tropical humid environment

The combined action of urbanization (change in land use) and increase in vehicular emissions intensifies the urban heat island (UHI) effect in many cities in the developed countries. The urban warming (UHI) enhances heat-stress-related diseases and ozone (O₃) levels due to a photochemical reaction. Even though UHI intensity depends on wind speed, wind direction, and solar flux, the thermodynamic properties of surface materials can accelerate the temperature profiles at the local scale. This mechanism modifies the atmospheric boundary layer (ABL) structure and mixing height in urban regions. These changes further deteriorate the local air quality. In this work, an attempt has been made to understand the interrelationship between air pollution and UHI intensity at selected urban areas located at tropical environment. The characteristics of ambient temperature profiles associated with land use changes in the different microenvironments of Chennai city were simulated using the Envi-Met model. The simulated surface 24-hr average air temperatures (11 m above the ground) for urban background and commercial and residential sites were found to be 30.81 ± 2.06, 31.51 ± 1.87, and 31.33 ± 2.1ºC, respectively. The diurnal variation of UHI intensity was determined by comparing the daytime average air temperatures to the diurnal air temperature for different wind velocity conditions. From the model simulations, we found that wind speed of 0.2 to 5 m/sec aggravates the UHI intensity. Further, the diurnal variation of mixing height was also estimated at the study locations. The estimated lowest mixing height at the residential area was found to be 60 m in the middle of night. During the same period, highest ozone (O₃) concentrations were also recorded at the continuous ambient air quality monitoring station (CAAQMS) located at the residential area.

Implications: An attempt has made to study the diurnal variation of secondary pollution levels in different study regions. This paper focuses mainly on the UHI intensity variations with respect to percentage of land use pattern change in Chennai city, India. The study simulated the area-based land use pattern with local mixing height variations. The relationship between UHI intensity and mixing height provides variations on local air quality.     

Critical review of the building downwash algorithms in AERMOD

The only documentation on the building downwash algorithm in AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model), referred to as PRIME (Plume Rise Model Enhancements), is found in the 2000 A&WMA journal article by Schulman, Strimaitis and Scire. Recent field and wind tunnel studies have shown that AERMOD can overpredict concentrations by factors of 2 to 8 for certain building configurations. While a wind tunnel equivalent building dimension study (EBD) can be conducted to approximately correct the overprediction bias, past field and wind tunnel studies indicate that there are notable flaws in the PRIME building downwash theory. A detailed review of the theory supported by CFD (Computational Fluid Dynamics) and wind tunnel simulations of flow over simple rectangular buildings revealed the following serious theoretical flaws: enhanced turbulence in the building wake starting at the wrong longitudinal location; constant enhanced turbulence extending up to the wake height; constant initial enhanced turbulence in the building wake (does not vary with roughness or stability); discontinuities in the streamline calculations; and no method to account for streamlined or porous structures.

Implications: This paper documents theoretical and other problems in PRIME along with CFD simulations and wind tunnel observations that support these findings. Although AERMOD/PRIME may provide accurate and unbiased estimates (within a factor of 2) for some building configurations, a major review and update is needed so that accurate estimates can be obtained for other building configurations where significant overpredictions or underpredictions are common due to downwash effects. This will ensure that regulatory evaluations subject to dispersion modeling requirements can be based on an accurate model. Thus, it is imperative that the downwash theory in PRIME is corrected to improve model performance and ensure that the model better represents reality.     

Convergence in carbon dioxide emissions and the role of growth and institutions: a parametric and non-parametric analysis

Environmental Economics and Policy Studies - This paper examines convergence of per capita carbon dioxide (CO2) emission for a panel of 124 countries taking into account the impact of economic...