Iran in transition.

Being the second-largest country in the Middle East, Iran has a long history of civilisation during which several dynasties have been overthrown and established and health-related structures have been reorganised. Iran has had the replacement of traditional practices with modern medical treatments, emergence of multiple pioneer scientists and physicians with great contributions to the advancement of science, environmental and ecological changes in addition to large-scale natural disasters, epidemics of multiple communicable diseases, and the shift towards non-communicable diseases in recent decades. Given the lessons learnt from political instabilities in the past centuries and the approaches undertaken to overcome health challenges at the time, Iran has emerged as it is today. Iran is now a country with a population exceeding 80 million, mainly inhabiting urban regions, and has an increasing burden of non-communicable diseases, including cardiovascular diseases, hypertension, diabetes, malignancies, mental disorders, substance abuse, and road injuries.

Quantifying Greenhouse Gas Emissions and the Marginal Cost of Carbon Abatement for Residential Buildings under California's 2019 Title 24 Energy Codes.

California's building energy codes (Title 24, Part 6), updated triennially since 1978, are the most stringent in the nation. The aim of California contemporary energy policy in general, and the state's building codes and standards in particular, is the reduction of greenhouse gas emissions. The state has identified residential designs that "bring value to the grid" as a key constituent of this effort. This research quantifies the marginal costs that code requirements add to new residential construction, the quantity of carbon emissions and abatement expected at a statewide level, and the marginal abatement cost of homes built under the new 2019 standards relative to those built under the prior code. We model hourly energy consumption and emissions (2020-2050) for seven residential building types representative of California production housing for each of California's 16 climate zones. Costs and benefits of each housing type are analyzed under a 30-year timeframe. Our results indicate that the 2019 code allows for a wide range of emission profiles, including very high long-term emissions resulting from the use of natural gas and under high leak rates. The significant and previously unreported impact of pre-meter natural gas leaks emphasizes the challenges that natural gas creates with respect to meeting California's long-term GHG reduction goals. Marginal abatement costs are dependent on natural gas leak rates, but consistently indicate that all-electric homes represent the first-best policy option for residential sector GHG abatement in California.

Calculating carbon emissions from personal travelling: insights from a top-down analysis of key calculators.

Personal travelling unfavourably contributes to the emissions of greenhouse gases, which adversely causes long-term damage to the climate. In order to reduce the associated negative impacts of such activities on the environment, there is a wide consensus that enhancements and innovations in the efficiency of vehicles will not be enough, but behavioural changes are needed. For this, individuals should be able to measure their travel-related carbon emissions, and such emissions could be determined by using personal carbon footprint calculators, which proliferated during the previous decade. However, various research questions related to such calculators are yet to be answered in published literature. As such, this paper investigates how key transport-based calculators account for emissions from personal transport-related activities following a top-down analysis. In this endeavour, ten such calculators are investigated through a set of formulated research questions to analyse their scope, calculation approach used, transparency, consistency of results, communication methods utilized and platform differences. Results revealed that the calculators have varying granularity, have limited transparency, provide significantly inconsistent results in some cases and are not fully engaging end users. Based on limitations identified, recommendations have been proposed through a taxonomy to guide policy-makers towards improving such tools.

Differences in rural and urban driver-injury severities in accidents involving large-trucks: an exploratory analysis.

This study explores the differences between urban and rural driver injuries (both passenger-vehicle and large-truck driver injuries) in accidents that involve large trucks (in excess of 10,000 pounds). Using 4 years of California accident data, and considering four driver-injury severity categories (no injury, complaint of pain, visible injury, and severe/fatal injury), a multinomial logit analysis of the data was conducted. Significant differences with respect to various risk factors including driver, vehicle, environmental, road geometry and traffic characteristics were found to exist between urban and rural models. For example, in rural accidents involving tractor-trailer combinations, the probability of drivers' injuries being severe/fatal increased about 26% relative to accidents involving single-unit trucks. In urban areas, this same probability increased nearly 700%. In accidents where alcohol or drug use was identified as being the primary cause of the accident, the probability of severe/fatal injury increased roughly 250% percent in rural areas and nearly 800% in urban areas. While many of the same variables were found to be significant in both rural and urban models (although often with quite different impact), there were 13 variables that significantly influenced driver-injury severity in rural but not urban areas, and 17 variables that significantly influenced driver-injury severity in urban but not rural areas. We speculate that the significant differences between rural and urban injury severities may be at least partially attributable to the different perceptual, cognitive and response demands placed on drivers in rural versus urban areas.

Impact of finer grid resolution on the spatial distribution of vehicle emissions inventories.

The ability to model air quality dispersion at increasingly smaller resolutions requires a concomitant improvement in the resolution of the gridded mobile source emissions used as input to these models. Two methods are currently used to allocate mobile emissions to grids; because of the limitations associated with these methods, their application is usually restricted to coarser grid resolutions. This paper uses a new mobile emissions inventory model (UCDrive) to explore the spatial distribution of mobile source emissions using finer grid cell resolutions. Our results indicate that the new model improves the precision of the spatial allocation of mobile source emissions, which in turn improves our ability to identify and implement pollutant control strategies.