RESUMO
The assumption that vegetation improves air quality is prevalent in scientific, popular, and political discourse. However, experimental and modeling studies show the effect of green space on air pollutant concentrations in urban settings is highly variable and context specific. We revisited the link between vegetation and air quality using satellite-derived changes of urban green space and air pollutant concentrations from 2,615 established monitoring stations over Europe and the United States. Between 2010 and 2019, stations recorded declines in ambient NO2, (particulate matter) PM10, and PM2.5 (average of -3.14% y-1), but not O3 (+0.5% y-1), pointing to the general success of recent policy interventions to restrict anthropogenic emissions. The effect size of total green space on air pollution was weak and highly variable, particularly at the street scale (15 to 60 m radius) where vegetation can restrict ventilation. However, when isolating changes in tree cover, we found a negative association with air pollution at borough to city scales (120 to 16,000 m) particularly for O3 and PM. The effect of green space was smaller than the pollutant deposition and dispersion effects of meteorological drivers including precipitation, humidity, and wind speed. When averaged across spatial scales, a one SD increase in green space resulted in a 0.8% (95% CI: -3.5 to 2%) decline in air pollution. Our findings suggest that while urban greening may improve air quality at the borough-to-city scale, the impact is moderate and may have detrimental street-level effects depending on aerodynamic factors like vegetation type and urban form.
RESUMO
Ecosystem service (ES) spatial modelling is a key component of the integrated assessments designed to support policies and management practices aiming at environmental sustainability. ESTIMAP ("Ecosystem Service Mapping Tool") is a collection of spatially explicit models, originally developed to support policies at a European scale. We based our analysis on 10 case studies, and 3 ES models. Each case study applied at least one model at a local scale. We analyzed the applications with respect to: the adaptation process; the "precision differential" which we define as the variation generated in the model between the degree of spatial variation within the spatial distribution of ES and what the model captures; the stakeholders' opinions on the usefulness of models. We propose a protocol for adapting ESTIMAP to the local conditions. We present the precision differential as a means of assessing how the type of model and level of model adaptation generate variation among model outputs. We then present the opinion of stakeholders; that in general considered the approach useful for stimulating discussion and supporting communication. Major constraints identified were the lack of spatial data with sufficient level of detail, and the level of expertise needed to set up and compute the models.
RESUMO
Sparkling wines have become a popular beverage in recent years, and the production of these wines is subject to adulteration during fermentation. This study investigated the stable carbon isotopic composition (expressed as delta(13)C) of the wine and of the CO(2) bubbles produced during the second fermentation for a number of sparkling wines produced in different countries around the world. Carbon isotope ratio analyses were used to estimate the addition of sugar obtained from C(4) plants (sugar cane or corn). The average delta(13)C values of the Brazilian brut, demi-sec, and doux sparkling wines were -20.5 +/- 1.2 per thousand (n = 18), -18.1 +/- 1.3 per thousand (n = 9), and -15.8 per thousand (n = 1), respectively. These values were statistically heavier (more positive carbon isotope ratio values) than the average delta(13)C of sparkling wines produced in other parts of South America (Argentina and Chile, -26.1 +/- 1.6 per thousand, n = 5) and Europe (France, Germany, Italy, Portugal, and Spain, -25.5 +/- 1.2 per thousand, n = 12), but not statistically different from sparkling wines produced in the United States or Australia. The most likely explanation for differences in the carbon isotope ratios of wines from these different regions is the addition of C(4) sugar during the production of some sparkling wines from Australia, Brazil, and the United States. The isotopic composition of the CO(2) bubbles (delta(13)C-CO(2)) followed similar trends. The average delta(13)C-CO(2) of most of the Brazilian and Argentine sparkling wines was -10.8 +/- 1.2 per thousand (n = 23), indicating that the likely source of carbon for the second fermentation was sugar cane. Conversely, the average delta(13)C-CO(2) of most of the sparkling wines produced in Chile and Europe was -22.0 +/- 1.2 per thousand (n = 13), suggesting that a different sugar (most likely sugar beet) was most used in the second fermentation. It was concluded that in many cases, the carbon isotope ratios of sparkling wine and CO(2) bubbles can provide valuable information about the sugar sources.
