No-tillage (NT), a practice that has been shown to increase carbon sequestration in soils, has resulted in contradictory effects on nitrous oxide (N 2 O) emissions. Moreover, it is not clear how mitigation practices for N 2 O emission reduction, such as applying nitrogen (N) fertilizer according to soil N reserves and matching the time of application to crop uptake, interact with NT practices. N 2 O fluxes from two management systems [conventional (CP), and best management practices: NT 1reduced fertilizer (BMP)] applied to a corn (Zea mays L.), soybean (Glycine max L.), winter-wheat (Triticum aestivum L.) rotation in Ontario, Canada, were measured from January 2000 to April 2005, using a micrometeorological method. The superimposition of interannual variability of weather and management resulted in mean monthly N 2 O fluxes ranging from À1.9 to 61.3 g N ha À1 day À1 . Mean annual N 2 O emissions over the 5-year period decreased significantly by 0.79 from 2.19 kg N ha À1 for CP to 1.41 kg N ha À1 for BMP. Growing season (May-October) N 2 O emissions were reduced on average by 0.16 kg N ha À1 (20% of total reduction), and this decrease only occurred in the corn year of the rotation. Nongrowing season (November-April) emissions, comprised between 30% and 90% of the annual emissions, mostly due to increased N 2 O fluxes during soil thawing. These emissions were well correlated (r 2 5 0.90) to the accumulated degree-hours below 0 1C at 5 cm depth, a measure of duration and intensity of soil freezing. Soil management in BMP (NT) significantly reduced N 2 O emissions during thaw (80% of total reduction) by reducing soil freezing due to the insulating effects of the larger snow cover plus corn and wheat residue during winter. In conclusion, significant reductions in net greenhouse gas emissions can be obtained when NT is combined with a strategy that matches N application rate and timing to crop needs.

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This review comprehensively examines scientific literature pertaining to human physiology during exercise, including mechanisms of heat formation and dissipation, heat stress on the body, the importance of skin temperature monitoring, the effects of clothing, and microclimatic measurements. This provides a critical foundation for microclimatologists and biometeorologists in the understanding of experiments involving human physiology. The importance of the psychological aspects of how an individual perceives an outdoor environment are also reviewed, emphasizing many factors that can indirectly affect thermal comfort (TC). Past and current efforts to develop accurate human comfort models are described, as well as how these models can be used to develop resilient and comfortable outdoor spaces for physical activity. Lack of suitable spaces plays a large role in the deterioration of human health due to physical inactivity, leading to higher rates of illness, heart disease, obesity and heat-related casualties. This trend will continue if urban designers do not make use of current knowledge of bioclimatic urban design, which must be synthesized with physiology, psychology and microclimatology. Increased research is required for furthering our knowledge on the outdoor human energy balance concept and bioclimatic design for health and well-being in urban areas.

This study assessed the performance of the COMFA outdoor thermal comfort model on subjects performing moderate to vigorous physical activity. Field tests were conducted on 27 subjects performing 30 min of steady-state activity (walking, running, and cycling) in an outdoor environment. The predicted COMFA budgets were compared to the actual thermal sensation (ATS) votes provided by participants during each 5-min interval. The results revealed a normal distribution in the subjects' ATS votes, with 82% of votes received in categories 0 (neutral) to +2 (warm). The ATS votes were significantly dependent upon sex, air temperature, short and long-wave radiation, wind speed, and metabolic activity rate. There was a significant positive correlation between the ATS and predicted budgets (Spearman's rho=0.574, P<0.01). However, the predicted budgets did not display a normal distribution, and the model produced erroneous estimates of the heat and moisture exchange between the human body and the ambient environment in 6% of the cases.