A health data led approach for assessing potential health benefits of green and blue spaces: Lessons from an Irish case study.

Research producing evidence-based information on the health benefits of green and blue spaces often has within its design, the potential for inherent or implicit bias which can unconsciously orient the outcomes of such studies towards preconceived hypothesis. Many studies are situated in proximity to specific or generic green and blue spaces (hence, constituting a green or blue space led approach), others are conducted due to availability of green and blue space data (hence, applying a green or blue space data led approach), while other studies are shaped by particular interests in the association of particular health conditions with presence of, or engagements with green or blue spaces (hence, adopting a health or health status led approach). In order to tackle this bias and develop a more objective research design for studying associations between human health outcomes and green and blue spaces, this paper discussed the features of a methodological framework suitable for that purpose after an initial, year-long, exploratory Irish study. The innovative approach explored by this study (i.e., the health-data led approach) first identifies sample sites with good and poor health outcomes from available health data (using data clustering techniques) before examining the potential role of the presence of, or engagement with green and blue spaces in creating such health outcomes. By doing so, we argue that some of the bias associated with the other three listed methods can be reduced and even eliminated. Finally, we infer that the principles and paradigm adopted by the health data led approach can be applicable and effective in analyzing other sustainability problems beyond associations between human health outcomes and green and blue spaces (e.g., health, energy, food, income, environment and climate inequality and justice etc.). The possibility of this is also discussed within this paper.

How Does the Amount and Composition of PM Deposited on Platanus acerifolia Leaves Change Across Different Cities in Europe?

Particulate matter (PM) deposited on Platanus acerifolia tree leaves has been sampled in the urban areas of 28 European cities, over 20 countries, with the aim of testing leaf deposited particles as indicator of atmospheric PM concentration and composition. Leaves have been collected close to streets characterized by heavy traffic and within urban parks. Leaf surface density, dimensions, and elemental composition of leaf deposited particles have been compared with leaf magnetic content, and discussed in connection with air quality data. The PM quantity and size were mainly dependent on the regional background concentration of particles, while the percentage of iron-based particles emerged as a clear marker of traffic-related pollution in most of the sites. This indicates that Platanus acerifolia is highly suitable to be used in atmospheric PM monitoring studies and that morphological and elemental characteristics of leaf deposited particles, joined with the leaf magnetic content, may successfully allow urban PM source apportionment.

An inventory of trees in Dublin city centre.

While urban areas are often considered to be comprised chiefly of artificial surfaces, they can contain a substantial portion of green space and a great diversity of natural habitats. These spaces include public parks, private gardens and street trees, all of which can provide valuable environmental services, such as improved air quality. Trees play a particular role in cities as they are often placed along roadsides and in the median strip of busy streets. As such they regulate access to sunshine, restrict airflow, provide shelter, scavenge air pollutants and manage noise at the street level. A tree planting policy can be an important part of a broader environmental strategy aimed at improving the quality of life in urban areas but this requires up-to-date knowledge of the current tree stock, which does not exist for Dublin. This article presents an inventory of trees in Dublin's city centre, defined as the area between the Grand and Royal canals. The results show that there are over 10,000 trees in the study area representing a density of 684 trees km-2 or one tree to approximately every 50 residents of the city centre. The tree canopy extent when in full foliage was nearly 1 km2 in extent or 6% of the study area. A more detailed analysis of those trees planted along streets shows little species variation but clear distinction in the sizes of trees, which is indicative of the age of planting. These data are used to estimate the carbon stored in Dublin's trees.

Land use change and population growth in the Morobe Province of Papua New Guinea between 1975 and 2000.

The relation between human population growth and land use change is much debated. Here we present a case study from Papua New Guinea where the population has increased from 2.3 million in 1975 to 5.2 million in 2000. Since 85% of the population relies on subsistence agriculture, population growth affects agricultural land use. We assessed land use change in the Morobe province (33,933 km2) using topographic maps of 1975 and Landsat TM images of 1990 and 2000. Between 1975 and 2000, agricultural land use increased by 58% and population grew by 99%. Most new agricultural land was taken from primary forest and the forest area decreased from 9.8 ha person(-1) in 1975 to 4.4 ha person(-1) in 2000. Total population change and total land use change were strongly correlated. Most of the agricultural land use change occurred on Inceptisols in areas with high rainfall (>2500 mm year(-1)) on moderate to very steep slopes (10-56%). Agricultural land use changes in logged-over areas were in the vicinity of populated places (villages), and in close proximity to road access. There was considerable variation between the districts but districts with higher population growth also had larger increases in agricultural areas. It is concluded that in the absence of improved farming systems the current trend of increased agriculture with rapid population growth is likely to continue.