Hematology and Some Biochemical Parameters of Wild Rodents in Pistachio Gardens of Kerman Province, Southeast Iran

Wild rodents were collected using live snap traps in pistachio gardens of Kerman Province, Southeast Iran from 2007 to 2009, then some physiological parameters of them were measured. The samples were identified as follow: Nesokia indica, Meriones persicus, Meriones lybicus and Tatera indica. Blood samples were obtained from the heart, then the blood parameters (glucose, cholesterol, triglyceride, total protein, HDL, red and white blood cell number) in wild species of rodents and laboratory rat were compared. The results showed that there were no significant differences in serum glucose, triglyceride, HDL and total protein levels among different experimental groups. The concentration of cholesterol in T. indica was more than that in N. indica (P < 0.01). The total numbers of red blood cells also showed significant difference between wild garden rodent species and laboratory rat (P < 0.01), while the numbers of white blood cells showed no significant difference.     

Grazing management effects on sediment, phosphorus, and pathogen loading of streams in cool-season grass pastures

Erosion and runoff from pastures may lead to degradation of surface water. A 2-yr grazing study was conducted to quantify the effects of grazing management on sediment, phosphorus (P), and pathogen loading of streams in cool-season grass pastures. Six adjoining 12.1-ha pastures bisected by a stream in central Iowa were divided into three treatments: continuous stocking with unrestricted stream access (CSU), continuous stocking with restricted stream access (CSR), and rotational stocking (RS). Rainfall simulations on stream banks resulted in greater ( < 0.10) proportions of applied precipitation and amounts of sediment and P transported in runoff from bare sites than from vegetated sites across grazing treatments. Similar differences were observed comparing vegetated sites in CSU and RS pastures with vegetated sites in CSR pastures. Bovine enterovirus was shed by an average of 24.3% of cows during the study period and was collected in the runoff of 8.3 and 16.7% of runoff simulations on bare sites in CSU pastures in June and October of 2008, respectively, and from 8.3% of runoff simulations on vegetated sites in CSU pastures in April 2009. Fecal pathogens (bovine coronavirus [BCV], bovine rotavirus group A, and O157:H7) shed or detected in runoff were almost nonexistent; only BCV was detected in feces of one cow in August of 2008. Erosion of cut-banks was the greatest contributor of sediment and P loading to the stream; contributions from surface runoff and grazing animals were considerably less and were minimized by grazing management practices that reduced congregation of cattle by pasture streams.     

Resolving local-scale emissions for modeling air quality near roadways

A large body of literature published in recent years suggests increased health risk due to exposure of people to air pollution in close proximity to roadways. As a result, there is a need to more accurately represent the spatial concentration gradients near roadways to develop mitigation strategies. In this paper, we present a practical, readily adaptable methodology, using a "bottom-up" approach to develop a detailed highway vehicle emission inventory that includes emissions for individual road links. This methodology also takes advantage of geographic information system (GIS) software to improve the spatial accuracy of the activity information obtained from a Travel Demand Model. In addition, we present an air quality modeling application of this methodology in New Haven, CT. This application uses a hybrid modeling approach, in which a regional grid-based model is used to characterize average local ambient concentrations, and a Gaussian dispersion model is used to provide texture within the modeling domain because of spatial gradients associated with highway vehicle emissions and other local sources. Modeling results show substantial heterogeneity of pollutant concentrations within the modeling domain and strong spatial gradients associated with roadways, particularly for pollutants dominated by direct emissions.     

Impact of underestimating the effects of cold temperature on motor vehicle start emissions of air toxics in the United States

Analyses of U.S. Environmental Protection Agency (EPA) certification data, California Air Resources Board surveillance testing data, and EPA research testing data indicated that EPA's MOBILE6.2 emission factor model substantially underestimates emissions of gaseous air toxics occurring during vehicle starts at cold temperatures for light-duty vehicles and trucks meeting EPA Tier 1 and later standards. An unofficial version of the MOBILE6.2 model was created to account for these underestimates. When this unofficial version of the model was used to project emissions into the future, emissions increased by almost 100% by calendar year 2030, and estimated modeled ambient air toxics concentrations increased by 6-84%, depending on the pollutant. To address these elevated emissions, EPA recently finalized standards requiring reductions of emissions when engines start at cold temperatures.