Academic literature on the topic 'Daisy pattern mitigation'

Urban heat island (UHI), referring to higher temperatures in urban extents than its surrounding rural regions, is widely reported in terms of negative effects to both the ecological environment and human health. To propose effective mitigation measurements, spatiotemporal variations and control machines of surface UHI (SUHI) have been widely investigated, in particular based on the indicator of SUHI intensity (SUHII). However, studies on SUHI frequency (SUHIF), an important temporal indicator, are challenged by a large number of missing data in daily land surface temperature (LST). Whether there is any city with strong SUHII and low SUHIF remains unclear. Thanks to the publication of daily seamless all-weather LST, this paper is proposed to investigate spatiotemporal variations of SUHIF, to compare SUHII and SUHIF, to conduct a pattern classification, and to further explore their driving factors across 305 Chinese cities. Four main findings are summarized below: (1) SUHIF is found to be higher in the south during the day, while it is higher in the north at night. Cities within the latitude from 20° N and 40° N indicate strong intensity and high frequency at day. Climate zone-based variations of SUHII and SUHIF are different, in particular at nighttime. (2) SUHIF are observed in great diurnal and seasonal variations. Summer daytime with 3.01 K of SUHII and 80 of SUHIF, possibly coupling with heat waves, increases the risk of heat-related diseases. (3) K-means clustering is employed to conduct pattern classification of the selected cities. SUHIF is found possibly to be consistent to its SUHII in the same city, while they provide quantitative and temporal characters respectively. (4) Controls for SUHIF and SUHII are found in significant variations among temporal scales and different patterns. This paper first conducts a comparison between SUHII and SUHIF, and provides pattern classification for further research and practice on mitigation measurements.

A key challenge in the twenty-first century is to enable economic growth and increase both environmentalquality and social inclusiveness, while mitigating and adapting to the impacts of climate change. The need for a transition to more sustainable consumption and production patterns is undeniable and sustainable economic growth must be placed at the heart of future development for all citizens. The South African private sector is under enormous pressure to remain globally competitive while balancing the interests of society, the environment and its shareholders. It has been suggested that there are discrepancies between what companies say and what they actually do, as they are challenged to move from policy to action. This paper evaluates the extent to which the private sector in South Africa adheres to voluntary climate change mitigation mechanisms and identifies potential market barriers impeding the large-scale uptake of such mechanisms. The research findings suggest that the private sector in South Africa has adopted a “take position, wait and see approach” which places them in a position to take advantage of and influence the opportunities and risks associated with climate change without having a negative impact on the bottom line. The primary barrier to voluntary climate change action is the vagueness of local and international policy frameworks. The different rules and resultant uncertainty around local and international frameworks appear to impede consistent and meaningful action. Although this uncertainty does not prevent the private sector from taking voluntary action, it does appear to negatively affect the overall scale and type of climate change mitigation efforts. While companies are continually improving the quality of sustainability reporting and public disclosure, the challenge still lies in translating these strategies into daily operations and sustainable practice that goes beyond ad hoc mitigation actions.

The number of road traffic accidents decreased in Lithuania from 2002 to 2017, while the ungulate–vehicle collision (UVC) number increased and accounted for approximately 69% of all wildlife–vehicle collisions (WVC) in the country. Understanding the relationship between UVCs, traffic intensity, and implemented mitigation measures is important for the assessment of UVC mitigation measure efficiency. We assessed the effect of annual average daily traffic (AADT) and wildlife fencing on UVCs using regression analysis of changes in annual UVCs and UVC hotspots on different categories of roads. At the highest rates, annual UVC numbers and UVC hotspots increased on lower category (national and regional) roads, forming a denser network. Lower rates of UVC increase occurred on higher category (main) roads, forming sparser road networks and characterized by the highest AADT. Before 2011, both UVC occurrence and fenced road sections were most common on higher-category roads. However, as of 2011, the majority of UVCs occurred on lower-category roads where AADT and fencing had no impact on UVCs. We conclude that wildlife fencing on roads characterized by higher speed and traffic intensity may decrease UVC numbers and at the same time shifting UVC occurrence towards roads characterized by lower speed and traffic intensity. Wildlife fencing re-allocates wildlife movement pathways toward roads with insufficient or no mitigation measures.

The mandate to limit global temperature rise calls for a reliable quantification of gaseous pollutant emissions as a basis for effective mitigation. Methane emissions from ruminant fermentation are of particular relevance in the context of greenhouse gas mitigation. The emission dynamics are so far insufficiently understood. We analyzed hourly methane emission data collected during contrasting seasons from two naturally ventilated dairy cattle buildings with concrete floor and performed a second order polynomial regression. We found a parabolic temperature dependence of the methane emissions irrespective of the measurement site and setup. The position of the parabola vertex varied when considering different hours of the day. The circadian rhythm of methane emissions was represented by the pattern of the fitted values of the constant term of the polynomial and could be well explained by feeding management and air flow conditions. We found barn specific emission minima at ambient temperatures around 10 °C to 15 °C. As this identified temperature optimum coincides with the welfare temperature of dairy cows, we concluded that temperature regulation of dairy cow buildings with concrete floor should be considered and further investigated as an emission mitigation measure. Our results further indicated that empirical modeling of methane emissions from the considered type of buildings with a second order polynomial for the independent variable air temperature can increase the accuracy of predicted long-term emission values for regions with pronounced seasonal temperature fluctuations.