Atmosphere2013, 4(4), 445-471; doi:10.3390/atmos4040445 - published online 5 December 2013 Show/Hide Abstract
Abstract: The presence of toxic substances such as persistent organic pollutants (POPs) in the environment, and in organisms including humans, is a serious public health and environmental problem, even at low levels and poses a challenging scientific problem. The Stockholm Convention on POPs (SC) entered into force in 2004 and is a large international effort under the United Nations Environment Programme (UNEP) to facilitate cooperation in monitoring, modeling and the design of effective and fair ways to deal with POPs globally. This paper is a contribution to the ongoing effectiveness evaluation (EE) work aimed at the assessment and enhancement of the effectiveness of the actions undertaken under the SC. First we consider some aspects related to the monitoring of POPs in the environment and then briefly review modeling frameworks that have been used to simulate long range transport (LRT) of POPs. In the final sections we describe the institutional arrangements providing the conditions for this work to unfold now and some suggestions for it in the future. A more effective use of existing monitoring data could be made if scientists who deposited them in publicly available and supervised sites were rewarded in academic and professional terms. We also suggest the development of multi-media, nested, Lagrangian models to improve the understanding of changes over time in the environment and individual organisms.
Atmosphere2013, 4(4), 428-444; doi:10.3390/atmos4040428 - published online 29 November 2013 Show/Hide Abstract
Abstract: Micrometeorological measurements were used to evaluate heat and water vapor to describe the transpiration (Ev) and soil evaporation (Es) processes for wide and narrow runoff strips under in-field rainwater harvesting (IRWH) system. The resulting sigmoid-shaped water vapor (ea) in wide and narrow runoff strips varied in lower and upper parts of the maize canopy. In wide runoff strips, lapse conditions of ea extended from lowest measurement level (LP) to the upper middle section (MU) and inversion was apparent at the top of the canopy. The virtual potential temperature (θv) profile showed no difference in middle section, but the lower and upper portion (UP) had lower in narrow, compared to wide, strips, and LP-UP changes of 0.6 K and 1.2 K were observed, respectively. The Ev and Es within the canopy increased the ea concentration as determined by the wind order of magnitude. The ea concentration reached peak at about 1.6 kPa at a range of wind speed value of 1.4–1.8 m∙s−1 and 2.0–2.4 m∙s−1 for wide and narrow treatments, respectively. The sparse maize canopy of the wide strips could supply more drying power of the air in response to atmospheric evaporative demand compared to narrow strips. This is due to the variation in air flow in wide and narrow runoff strips that change gradients in ea for evapotranspiration processes.
Atmosphere2013, 4(4), 411-427; doi:10.3390/atmos4040411 - published online 13 November 2013 Show/Hide Abstract
Abstract: This paper investigates the relationship between the Normalized Difference Vegetation Index (NDVI) and extracted rainfall in the Global Precipitation Climatology Project (GPCP) in Central Africa between latitudes 15°S and 20°N and longitudes 0°E and 31°E. Monthly NDVI and GPCP datasets for the period 1982–2000 have been used. The Index of Segmentation of Fourier Components (ISFC) has been applied on the NDVI dataset to segment Central Africa into four bioclimatic ecoregions (BCERs). In order to compare the differential response of vegetation growth to rainfall, an analysis of the inter-annual, intra-annual and seasonal variability for each BCER has been carried out, and the correlations between NDVI and rainfall have been assessed. The plot of the annual cycles of both variables revealed a coherent onset, peak and decay, with a time lag of 1 month for almost all the zones, except the zones, semi-desert and steppe, where a season of short and intense rainfall was observed. The correlation coefficients computed between the two variables are relatively high, especially in brush-grass savannah, where they reach up to 0.90 at a time lag of 1 month. The phenological transition points and phases show that the range between the +1 and
Atmosphere2013, 4(4), 383-410; doi:10.3390/atmos4040383 - published online 13 November 2013 Show/Hide Abstract
Abstract: The variety of natural indicators, associated with weather forecasting and climate prediction, as used by farmers in the South-Western Free State province of South Africa, is described. Most farmers in this area were not familiar with the application of weather forecasts/climate predictions for agricultural production, or with other science-based agrometeorological products. They relied almost fully on their experience and traditional knowledge for farming decision making. The indicators for traditional knowledge are demonstrated here in broad terms, relying on the stories and indications from observations and years of experience of their use by the farmers. These means of engagement with the natural environment, are skills not well understood by most scientists, but useful to the farmers. They range from the constellation of stars, animal behavior, cloud cover and type, blossoming of certain indigenous trees, appearance and disappearance of reptiles, to migration of bird species and many others. It is suggested that some short-term traditional forecasts/predictions may be successfully merged with science-based climate predictions. The traditional knowledge and its use, reported on in this paper, is what scientists learned from farmers. Berkes was right that scholars have wasted too much time and effort on a science versus traditional knowledge debate; we should reframe it instead as a science and traditional knowledge dialogue and partnership. The complications of a changing climate make this even more necessary.
Atmosphere2013, 4(4), 365-382; doi:10.3390/atmos4040365 - published online 8 November 2013 Show/Hide Abstract
Abstract: A new methodology to extract crop yield response to climate variability and change from long-term crop yield observations is presented in this study. In contrast to the existing first-difference approach (FDA), the proposed methodology considers that the difference in value between crop yields of two consecutive years reflects necessarily the contributions of climate and management conditions, especially at large spatial scales where both conditions may vary significantly from one year to the next. Our approach was applied to remove the effect of non-climatic factors on crop yield and, hence, to isolate the effect of the observed climate change between 1961 and 2006 on three widely crops grown in three Mediterranean countries—namely wheat, corn and potato—using national-level crop yield observations’ time-series. Obtained results show that the proposed methodology provides us with a ground basis to improve substantially our understanding of crop yield response to climate change at a scale that is relevant to large-scale estimations of agricultural production and to food security analyses; and therefore to reduce uncertainties in estimations of potential climate change effects on agricultural production. Furthermore, a comparison of outputs of our methodology and FDA outputs yielded a difference in terms of maize production in Egypt, for example, that exceeds the production of some neighbouring countries.
Atmosphere2013, 4(4), 349-364; doi:10.3390/atmos4040349 - published online 7 November 2013 Show/Hide Abstract
Abstract: The air quality in Taiwan, at present, is determined by a pollution standard index (PSI) that is applied to areas of possible serious air pollution and Air Quality Total Quantity Control Districts (AQTQCD). Many studies, both in Taiwan and in other countries have examined the characteristics and levels of air pollution with PSI. This study uses air quality data collected from eight automatic air quality monitoring stations in an AQTQCD in central Taiwan and discusses the correlation between air quality variables with statistical analysis in an attempt to accurately reflect the difference of air quality observed by each monitoring station as well as to establish an air quality classification system suitable for the whole Taiwan. After using factor analysis (FA), seven air pollutants are grouped into three factors: organic, photochemical, and fuel. These three factors are the dominant ones in regards to the air quality of central Taiwan. Cluster analysis is used to classify air quality in central Taiwan into five clusters to present different characteristics and pollution degrees of air quality. This research results should serve as a reference for those involved in the review of air quality management effectiveness and/or the enactment of management control strategies.