Regional dust storm modeling for health services: The case of valley fever

On 5 July 2011, a massive dust storm struck Phoenix, Arizona (USA), raising concerns for increased cases of valley fever (coccidioidomycosis, or, cocci). A quasi-operational experimental airborne dust forecast system predicted the event and provides model output for continuing analysis in collaboration with public health and air quality communities. An objective of this collaboration was to see if a signal in cases of valley fever in the region could be detected and traced to the storm - an American haboob. To better understand the atmospheric life cycle of cocci spores, the DREAM dust model (also herein, NMME-DREAM) was modified to simulate spore emission, transport and deposition. Inexact knowledge of where cocci-causing fungus grows, the low resolution of cocci surveillance and an overall active period for significant dust events complicate analysis of the effect of the 5 July 2011 storm. In the larger context of monthly to annual disease surveillance, valley fever statistics, when compared against PM10 observation networks and modeled airborne dust concentrations, may reveal a likely cause and effect. Details provided by models and satellites fill time and space voids in conventional approaches to air quality and disease surveillance, leading to land-atmosphere modeling and remote sensing that clearly mark a path to advance valley fever epidemiology, surveillance and risk avoidance

Numerical simulation of Tehran dust storm on 2 june 2014: A case study of agricultural abandoned lands as emission sources

On 2 June 2014, at about 13 UTC, a dust storm arrived in Tehran as a severe hazard that caused injures, deaths, failures in power supply, and traffic disruption. Such an extreme event is not considered as common for the Tehran area, which has raised the question of the dust storm’s origin and the need for increasing citizens’ preparedness during such events. The analysis of the observational data and numerical simulations using coupled dust-atmospheric models showed that intensive convective activity occurred over the south and southwest of Tehran, which produced cold downdrafts and, consequently, high-velocity surface winds. Different dust source masks were used as an input for model hindcasts of the event (forecasts of the past event) to show the capability of the numerical models to perform high-quality forecasts in such events and to expand the knowledge on the storm’s formation and progression. In addition to the proven capability of the models, if engaged in operational use to contribute to the establishment of an early warning system for dust storms, another conclusion appeared as a highlight of this research: abandoned agricultural areas south of Tehran were responsible for over 50% of the airborne dust concentration within the dust storm that surged through Tehran. Such a dust source in the numerical simulation produced a PM10 surface dust concentration of several thousand µm/m3, which classifies it as a dust source hot-spot. The produced evidence indivisibly links issues of land degradation, extreme weather, environmental protection, and health and safety

ODREĐIVANJE SREDNJE DISTANCE PRIVLAČENJA PRIMJENOM GIS-A U NIZIJSKO-BRDSKIM USLOVIMA

Transport sortimenata, prije svega oblog drveta, je najskuplji proces u proizvodnji. On se sastoji iz trifaze: primicanje, privlačenje i prevoz kamionima. Sa stanovišta troškova transporta najvažnije su prvedvije faze transporta. One u prvom redu zavise od udaljenosti mjesta sječe stabala od šumskog putaili srednje transportne distance privlačenja i zato je određivanje njene vrijednosti veoma važno sastanovišta planiranja otvorenosti šuma. Srednja transportna distanca je jedan od pokazatelja otvorenosti.Vrijednost srednje transportne distance privlačenja može se dobiti na više načina: mjerenjemna terenu ili pomoću programskih paketa zasnovanih na GIS-u. Srednja transportna distanca dobijenau Izvođačkim projektima za odjele 19, 20, 21, 22, 37, 47, 48 i 22/1 u Privrednoj jedinici „Prosara“,iznosi 600 m. Primjenom ArcGIS 10 programskog paketa dobijena je prvo geometrijska transportnadistanca privlačenja koju smo množili sa faktorom korekcije koji za date terenske uslove iznosi 1,38. Nataj način smo dobili stvarnu srednju transportnu distancu privlačenja koja je 590 m. Između ove dvijedaljine privlačenja nema statistički značajne razlike i prema tome srednja stvarna transportna distancaprivlačenja koja je određena pomoću ArcGIS-a 10, može biti korišćena za određivanje učinka skidera.Uporedili smo stvarnu i geometrijsku srednju transportnu distancu privlačenja i dobili da faktor korekcijeiznosi 1,57. Prema tome prosječni faktor korekcije za nizijsko-brdske terene iznosi 1,475