Ozone Predictions in Atlanta,Georgia: Analysis of the 1999 Ozone Season

ABSTRACT

Ozone prediction has become an important activity in many U.S. ozone nonattainment areas. In this study, we describe the ozone prediction program in the Atlanta metropolitan area and analyze the performance of this program during the 1999 ozone-forecasting season. From May to September, a team of 10 air quality regulators, meteorologists, and atmospheric scientists made a daily prediction of the next-day maximum 8-hr average ozone concentration. The daily forecast was made aided by two linear regression models, a 3-dimensional air quality model, and the no-skill ozone persistence model. The team's performance is compared with the numerical models using several numerical indicators. Our analysis indicated that (1) the team correctly predicted next-day peak ozone concentrations 84% of the time, (2) the two linear regression models had a better performance than a 3-dimensional air quality model, (3) persistence was a strong predictor of ozone concentrations with a performance of 78%, and (4) about half of the team's wrong predictions could be prevented with improved meteorological predictions.     

Modified Whittaker plots as an assessment and monitoring tool for vegetation in a lowland tropical rainforest

Resource exploitation in lowland tropical forests is increasingand causing loss of biodiversity. Effective evaluation and management of the impacts of development on tropical forests requires appropriate assessment and monitoring tools. We proposethe use of 0.1-ha multi-scale, modified Whittaker plots (MWPs) to assess and monitor vegetation in lowland tropical rainforests.We established MWPs at 4 sites to: (1) describe and comparecomposition and structure of the sites using MWPs, (2) compare these results to those of 1-ha permanent vegetation plots (BDPs),and (3) evaluate the ability of MWPs to detect changes in populations (statistical power). We recorded more than 400 species at each site. Species composition among the sites was distinctive, while mean abundance and basal area was similar. Comparisons between MWPs and BDPs show that they record similarspecies composition and abundance and that both perform equallywell at detecting rare species. However, MWPs tend to record morespecies, and power analysis studies show that MWPs were more effective at detecting changes in the mean number of species of trees 10 cm in diameter at breast height (dbh) and in herbaceous plants. Ten MWPs were sufficient to detect a change of 11% in the mean number of herb species, and they were able to detect a 14% change in the mean number of species of trees 10 cm dbh. The value of MWPs for assessment and monitoringis discussed, along with recommendations for improving the sampling design to increase power.     

Construction Job Safety Analysis

Job Safety Analysis (JSA), which is also known as Job Hazard Analysis, is an efficient proactive measure for safety risk assessment used in industrial manufacturing settings. However, unlike the manufacturing settings for which JSA was developed, at construction sites the physical environment is constantly changing, workers move through the site in the course of their work, and they are often endangered by activities performed by other teams. To address this difficulty, a structured method for hazard analysis and assessment for construction activities, called “Construction Job Safety Analysis” (CJSA), was developed. The method was developed within the framework of research toward a lean approach to safety management in construction, which required the ability to predict fluctuating safety risk levels in order to support safety conscious planning and pulling of safety management efforts to the places and times where they are most effective. The method involves identification of potential loss-of-control events for detailed stages of the activities commonly performed in construction, and assessment of the probability of occurrence for each event identified. It was applied to explore 14 primary construction activities in an extensive trial implementation that included expert workshops and a series of 101 interviews with site engineers and superintendents. Detailed quantitative results were obtained for a total of 699 possible loss-of-control events; the most frequent events are those related to exterior work at height.     

Biocapacity convergence clubs in Latin America: an analysis of their determining factors using quantile regressions

Latin America experiences an increasing urban primacy index and a rapid expansion of the financial system, putting direct pressure on the demand for resources to satisfy the consumption of large cities. We investigate the convergence of per capita biocapacity in 16 Latin America countries and evaluate the factors that influence its evolution over time. Specifically, we analyze the impact of the urban primacy index, economic progress, and the financial globalization index on the convergence of per capita biocapacity. We use the methodological framework developed by Phillips and Sul Econometrica 75:1771-1855, (2007) to analyze the convergence and the formation of convergence clubs of biocapacity during 1970–2017. The findings indicate that the countries of the region do not share a common trend of biocapacity, although they are grouped into five converging clubs. Biocapacity transition analysis reveals that countries have heterogeneous transition pathways between them. Using marginal effects, we find that the urban primacy index and economic progress reduce the biocapacity. The effect of the financial globalization index on biocapacity is not conclusive. The quantile regressions reveal that quantiles’ impact of the urban primacy index and financial globalization on per capita biocapacity is heterogeneous. However, the effect of economic progress on biocapacity that predominates among quantiles is positive. The adoption of common policies among the countries that form the converging clubs could improve the effectiveness of pro-environmental policies and promote the achievement of the Sustainable Development Goals related to environmental quality.