The 2007 crisis and Greek wildfires: a multivariate analysis of suppression times

Shifts in government priorities in response to the 2007 global recession have affected wildfire management and natural disaster funding arrangements, leading to a reduced effectiveness of fire suppression actions and increasing fire vulnerability. Our study investigates the role of local socioeconomic contexts on fire suppression effectiveness under economic expansion and recession in a Mediterranean region (Attica, Greece) strongly affected by 2007 crisis and displaying a persistently high density of peri-urban wildfires. Basic characteristics of wildfires (spatial distribution, intensity, and land use preferences) were investigated in the study area over two consecutive 8-year time intervals characterized by economic expansion (2000–2007) and recession (2008–2015). An integrated approach based on multivariate statistics and artificial neural networks was implemented to evaluate latent relationships between fire suppression time, wildfire characteristics, and socioeconomic dynamics. Controlling for wildfires’ characteristics over the two time intervals, fire time length increased under crisis—mainly for small and medium-sized fires—possibly as an indirect response to reduced effectiveness of forest land management. Local contexts and political decisions influenced by economic downturns are relevant factors shaping wildfires’ severity in the Mediterranean region. With recession, local contexts vulnerable to wildfires require more effective fire prevention measures, sustainable forest management, and regional planning.     

A study of fatal pedestrian crashes at rural low-volume road intersections in southwest China

Objective: Although intersections correspond to a small proportion of the entire roadway system, they account for a disproportionally high number of fatal pedestrian crashes, especially on rural roads situated in low- and middle-income countries. This article examines pedestrian safety at rural intersections and suggests applicable accident prevention treatments by providing an in-depth analysis of 28 fatal pedestrian crashes from 8 low-volume roads in southwest China.

Methods: The driving reliability and error analysis method (DREAM) is a method to support a systematic classification of accident causation information and to facilitate aggregation of that information into patterns of contributing factors. This is the first time that DREAM was used to analyze pedestrian–vehicle crashes and provide suggestions for road improvements in China.

Results: The key issues adversely affecting pedestrian safety can be organized in 4 distinctive thematic categories, namely, deficient intersection safety infrastructure, lack of pedestrian safety education, inadequate driver training, and insufficient traffic law enforcement. Given that resources for traffic safety investments in rural areas are limited, it is determined that the potential countermeasures should focus on low-cost, easily implementable, and long-lasting measures increasing the visibility and predictability of pedestrian movement and reducing speeding and irresponsible driving among drivers and risk-taking behaviors among pedestrians.

Conclusions: Accident prevention treatments are suggested based on their suitability for rural areas in southwest China. These countermeasures include introducing better access management and traffic calming treatments, providing more opportunities for pedestrian education, and enhancing the quality of driver training and traffic law enforcement.     

Evaluating Japanese policy instruments for the promotion of renewable energy sources

In Japan, the Renewable Portfolio Standard (RPS) and the Feed-in-Tariff (FIT) have been used for the exploitation of renewable energy sources (RES). Although these are significant to enhance the use of RES, the RES penetration is not reaching the expected percentage. The identification of their strengths/weaknesses will allow their improvement for achieving the target. This paper concerned the evaluation of RPS and FIT using a multi-criteria evaluation method. First, official data/information were used to assess their performance using the method. Second, national experts were asked about their performance to verify the outcomes. We found FIT was more effective than RPS.     

Predicting photochemical pollution in an industrial area

In order to confront pollution events concerning the city of Elefsis, in the environmentally aggravated area of Thriassion Plain, an effort is undertaken to create a model forecasting maximal daily concentrations of NO(x) (NO(2)+NO), NO(2) and O(3). The data analyzed were obtained from the Bureau of Pollution Control and Environments Quality based in Elefsis. The model in question uses hourly values of the pollutants as well as meteorological data recorded at the center of the city of Elefsis from 1993 to 1999. Three fitting methods are utilized, namely ordinary least squares, piecewise, and quantile regression. The verification and reliability of the forecasting models are based on the measurements of the year 2000. The results are considered to be satisfactory, with the forecasted values following the general tendencies.