The relationship between temperature and digital hate – strong increase of racist tweets outside of climate comfort zone in Europe

2021 ◽  
Author(s):  
Annika Stechemesser ◽  
Leonie Wenz ◽  
Maximilian Kotz ◽  
Anders Levermann
Keyword(s):  
Fixed Effects ◽  
Well Being ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Strong Increase ◽  
Daily Maximum ◽  
Increased Risk ◽  
The World ◽  
The Impact ◽  
The Relationship

<p>Temperature has been identified as a potential cause for human conflict. Conflict poses a fundamental obstacle to Sustainable Development Goal 16 which acknowledges the importance of building peace, justice and strong institutions for people around the world. Today, conflict is no longer limited to the physical space. The increasing digitalization of all areas of everyday life reinforces the impact of cyber racism, cyber discrimination and online hate. It disproportionally affects groups with an already increased risk of marginalization such as women, lgbtq+ youth or people of color, causing affected persons to feel unsafe in digital spaces and limiting their access to online services. Twitter is one of the biggest social media platforms with more than 300 million active users around the world. We provide evidence that the amount of racist content posted to Twitter is non-linearly influenced by temperature. Exploiting the linguistic plurality of Europe, we investigate the relationship between daily maximum temperature and racist or xenophobic content online using a fixed-effects panel-regression approach for countries spanning multiple European climatic zones. Racist tweets are lowest between daily temperatures of 8°C to 17°C whereas ambient temperatures warmer or colder are associated with steep, non-linear increases. Within the next 30 years, temperatures are projected to shift with new heat extremes being reached. To quantify the potential impact on cyber hate, the number of days outside this range, weighted by the identified temperature-racist-tweet response curve is projected to increase across Europe. Results suggest, that future warming and more extreme temperatures could aggravate xenophobia and racism online, further hindering the achievement of SDG 16 and posing a challenge for future human well-being.  </p>

scholarly journals Social media reveal ecoregional variation in how weather influences visitor behavior in U.S. National Park Service units

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emily J. Wilkins ◽  
Peter D. Howe ◽  
Jordan W. Smith
Keyword(s):  
National Park ◽  
National Park Service ◽  
Spatial Behavior ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Daily Weather ◽  
Visitor Behavior ◽  
Park Service ◽  
The Impact

AbstractDaily weather affects total visitation to parks and protected areas, as well as visitors’ experiences. However, it is unknown if and how visitors change their spatial behavior within a park due to daily weather conditions. We investigated the impact of daily maximum temperature and precipitation on summer visitation patterns within 110 U.S. National Park Service units. We connected 489,061 geotagged Flickr photos to daily weather, as well as visitors’ elevation and distance to amenities (i.e., roads, waterbodies, parking areas, and buildings). We compared visitor behavior on cold, average, and hot days, and on days with precipitation compared to days without precipitation, across fourteen ecoregions within the continental U.S. Our results suggest daily weather impacts where visitors go within parks, and the effect of weather differs substantially by ecoregion. In most ecoregions, visitors stayed closer to infrastructure on rainy days. Temperature also affects visitors’ spatial behavior within parks, but there was not a consistent trend across ecoregions. Importantly, parks in some ecoregions contain more microclimates than others, which may allow visitors to adapt to unfavorable conditions. These findings suggest visitors’ spatial behavior in parks may change in the future due to the increasing frequency of hot summer days.

scholarly journals The effects of ambient temperature and heatwaves on dailyCampylobactercases in Adelaide, Australia, 1990–2012

2017 ◽  
Vol 145 (12) ◽  
pp. 2603-2610 ◽  
Author(s):  
A. MILAZZO ◽  
L. C. GILES ◽  
Y. ZHANG ◽  
A. P. KOEHLER ◽  
J. E. HILLER ◽  
...  
Keyword(s):  
Regression Models ◽  
South Australia ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Infectious Gastroenteritis ◽  
Food Borne ◽  
Relationship Of ◽  
The Relationship

SUMMARYCampylobacterspp. is a commonly reported food-borne disease with major consequences for morbidity. In conjunction with predicted increases in temperature, proliferation in the survival of microorganisms in hotter environments is expected. This is likely to lead, in turn, to an increase in contamination of food and water and a rise in numbers of cases of infectious gastroenteritis. This study assessed the relationship ofCampylobacterspp. with temperature and heatwaves, in Adelaide, South Australia.We estimated the effect of (i) maximum temperature and (ii) heatwaves on dailyCampylobactercases during the warm seasons (1 October to 31 March) from 1990 to 2012 using Poisson regression models.There was no evidence of a substantive effect of maximum temperature per 1 °C rise (incidence rate ratio (IRR) 0·995, 95% confidence interval (95% CI) 0·993–0·997) nor heatwaves (IRR 0·906, 95% CI 0·800–1·026) onCampylobactercases. In relation to heatwave intensity, which is the daily maximum temperature during a heatwave, notifications decreased by 19% within a temperature range of 39–40·9 °C (IRR 0·811, 95% CI 0·692–0·952). We found little evidence of an increase in risk and lack of association betweenCampylobactercases and temperature or heatwaves in the warm seasons. Heatwave intensity may play a role in that notifications decreased with higher temperatures. Further examination of the role of behavioural and environmental factors in an effort to reduce the risk of increasedCampylobactercases is warranted.

scholarly journals Relationship beetwen the phenological features of pear cultivars and the main meteorological parameters in a gene bank with 555 pear

2009 ◽  
Vol 15 (1-2) ◽  
Author(s):  
L. Lakatos ◽  
S. Musacchi ◽  
T. Szabó ◽  
G. Kocsisné Molnár ◽  
Z. Szabó ◽  
...  
Keyword(s):  
Gene Bank ◽  
Meteorological Variables ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Night Time ◽  
Correlation And Regression Analysis ◽  
Fruit Growing ◽  
Autumn And Winter ◽  
The Relationship

The trees observed are grown at Ujfehert6, Eastern Hungary in a gene bank with 555 pear cultivars. Each of the cultivars was monitored for its dates of: the beginning of bloom, main bloom and the end of bloom and ripe phenophasis separately between I 984 and 2002. We analyzed the statistical features, frequency, distribution of these phenophasis and its' correlation the meteorological variables bet ween the interval. During this period the meteorological database recorded the following variables: daily mean temperature (°C), daily maximum temperature (0C), daily mini m um temperature (0C), daily precipitation (mm), daily hours of bright sunshine, daily means or the differences between the day-time and night-time temperatures (0C). For the analysis of data the cultivars have been grouped according to dates of maturity, blooming period as well as types of the seasons. Groups of maturity dates: summer ripe, autumnal ripening, winter ripe cultivars. Groups of blooming dates: early blooming, intermediate blooming, late blooming cultivars. At all the separated groups we analyzed the relationship between phenophasis and meteorological variables. During the 18 years of observation , the early blooming cultivars started blooming on 10-21 April, those of intermediate bloom date started flowering bet ween 20 April and 3 May, whereas the late blooming group started on 2- 10 May. Among the meteorological variables of the former autumn and winter periods, the winter maxima were the most active factor influencing the start dates of bloom in the subsequent spring. For the research of fruit growing-weather relationships we used simple, well known statistical methods, correlation and regression analysis. We used the SPSS 1 1.0 software for the linear regression fitting and for calculation of dispersions as well. The 1ables made by Excel programme.

scholarly journals The Associations Between Preceptor Team Lead Relationships and Resident Wellness in an Academic Medicine Setting: An Exploratory Study

PRiMER ◽  
2017 ◽  
Vol 1 ◽  
Author(s):  
Cesar A. Gonzalez ◽  
Natalie E Gentile ◽  
Kurt B Angstman ◽  
Julia R Craner ◽  
Robert P. Bonacci
Keyword(s):  
Family Medicine ◽  
Self Care ◽  
Well Being ◽  
Increased Risk ◽  
Resident Wellness ◽  
Team Based Care ◽  
Perception Of Support ◽  
The Impact ◽  
The Relationship ◽  
Family Medicine Residents

Background: Lack of wellness among physicians has been associated with increased risk for physical and mental illness, interpersonal discord, and occupational liability. In academic primary care practices, physician wellness and self-care behaviors have been associated with improved patient outcomes. With the increase in team-based care structures in primary care clinics and residencies there may be opportunities to promote wellness among primary clinicians, particularly among resident physicians who are at increased risk for decreased well being. The primary objective of the study was to test an a priori hypothesis that family medicine residents’ perception of support from preceptor team leads would be associated with wellbeing. A secondary objective of the study was to test a post hoc hypothesis that examined whether the relationship between residents’ perception of support from their preceptor team leads would be associated with residents’ well being, while controlling for self-care behaviors. Methods: Our study utilized a prospective cross-sectional design with purposive sampling to survey family medicine residents. Data were collected in February 2016. The survey was sent out to 58 family medicine residents across three family medicine residencies at Mayo Clinic. The survey response rate was 55% (n=32); Ten (31.3%) residents reported being in their PGY-1, 11 (34.4%) in PGY-2; and 11 (34.4%) in PGY-3; participants included 19 (59.4%) women and 13 (40.6%) men. The Brief Resident Wellness Profile (BRWP) was utilized to assess family medicine residents’ perceived sense of professional accomplishment and mood in the past week. Results: In bivariate correlational analyses, increased perception of support from preceptor team leads (r=.40, P<.01) and reporting a male gender (r=.43, P<.01) was associated with increased resident wellness. In exploratory multivariate analysis, results suggested that while controlling for gender, frequency of self-care behaviors, and perceived preceptor team lead support, a one-point change on rating of perceived team leader support is associated with a 1.69 increase in resident wellness score on the BRWP. Conclusions: Our results provide preliminary evidence to support the relationship between preceptor team lead support and resident wellness in team-based care, above and beyond the impact that self-behaviors have on wellness. Our findings suggest evidence for the subsequent study of the impact of preceptor team lead relationship quality on resident wellness. 

scholarly journals Meteorological factors affecting the risk of transmission of HPAI in Miyazaki, Japan

2019 ◽  
Vol 6 (1) ◽  
pp. e000341 ◽  
Author(s):  
Genki Arikawa ◽  
Yoshinori Fujii ◽  
Maiku Abe ◽  
Ngan Thi Mai ◽  
Shuya Mitoma ◽  
...  
Keyword(s):  
Bird Migration ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Migratory Waterfowl ◽  
Generalised Linear Mixed Model ◽  
Fulica Atra ◽  
The Relationship

Highly pathogenic avian influenza (HPAI) outbreaks engender a severe economic impact on the poultry industry and public health. Migratory waterfowl are considered the natural hosts of HPAI virus, and HPAI viruses are known to be transmitted over long distances during seasonal bird migration. Bird migration is greatly affected by the weather. Many studies have shown the relationship between either autumn or spring bird migration and climate. However, few studies have shown the relationship between annual bird migration and annual weather. This study aimed to establish a model for the number of migratory waterfowl involved in HPAI virus transmission based on meteorological data. From 136 species of waterfowl that were observed at Futatsudate in Miyazaki, Japan, from 2008 to 2016, we selected potential high-risk species that could introduce the HPAI virus into Miyazaki and defined them as ‘risky birds’. We also performed cluster analysis to select meteorological factors. We then analysed the meteorological data and the total number of risky birds using a generalised linear mixed model. We selected 10 species as risky birds: Mallard (Anas platyrhynchos), Northern pintail (Anas acuta), Eurasian wigeon (Anas penelope), Eurasian teal (Anas crecca), Common pochard (Aythya ferina), Eurasian coot (Fulica atra), Northern shoveler (Anas clypeata), Common shelduck (Tadorna tadorna), Tufted duck (Aythya fuligula) and Herring gull (Larus argentatus). We succeeded in clustering 35 meteorological factors into four clusters and identified three meteorological factors associated with their migration: (1) the average daily maximum temperature; (2) the mean value of global solar radiation and (3) the maximum daily precipitation. We thus demonstrated the relationship between the number of risky birds and meteorological data. The dynamics of migratory waterfowl was relevant to the risk of an HPAI outbreak, and our data could contribute to cost and time savings in strengthening preventive measures against epidemics.

Can trade help with fighting the pandemic? Evidence from imports of Chinese medical products

2021 ◽  
Vol 18 (2) ◽  
pp. 207-222
Author(s):  
Laike Yang ◽  
Bo Xu
Keyword(s):  
Negative Correlation ◽  
Fixed Effects ◽  
Significant Negative Correlation ◽  
Vital Role ◽  
Fixed Effects Model ◽  
Medical Products ◽  
The World ◽  
Percent Increase ◽  
The Impact ◽  
The Relationship

To contain the COVID-19 pandemic, medical products play an important role around the world. This paper studies the relationship between trade and pandemic control by testing the impact of importing medical products from China on COVID-19 cases and deaths. Using a fixed-effects model, we find that there is a significant negative correlation between imports of medical products from China and COVID-19 cases; for every 1 percent increase in protection equipment imported from China, new COVID-19 cases per day drop by 0.24 percent, and COVID-19-related deaths decrease by 0.13 percent in two weeks. The evidence suggests that trade can play a vital role in fighting the pandemic.

Impact of mass human migration during Chinese New Year on Beijing urban heat island

2020 ◽  
Author(s):  
Jingjing Dou ◽  
Shiguang Miao
Keyword(s):  
Spatial Distribution ◽  
Urban Heat Island ◽  
Human Migration ◽  
Floating Population ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Heat Island ◽  
Urban Heat ◽  
The Impact

<p>The Chinese New Year (CNY, also called Spring Festival), which officially lasts for 7 days, is the most important holiday in China. Chinese people in large cities usually return to their hometowns for family reunions before the CNY holiday and return afterward. Nearly half of Beijing’s population has been reported to leave the city for family reunions before the CNY holidays in the past several years. Hourly automatic weather station (AWS) data during CNY 2010-2015 were used to analyze the changes in the temporal and spatial distribution of the Beijing urban heat island intensity (UHII) and the impact of mass human migration on urban temperature. Soil moisture, 10-m wind speed, and cloud cover were considered and indicated nearly no change during the pre-CNY period (2 to 4 weeks before CNY) and CNY week, which means that UHII variation was mainly affected by the mass human migration. Daily UHII during CNY week was lower than during pre-CNY period. UHII for daily maximum temperature decreased by 55% during CNY week than the pre-CNY period (0.6 °C during pre-CNY period vs. 0.27 °C during CNY week) due to mass human migration, which was much larger than the reduction in UHII for the daily maximum temperature (5%, 4.34 °C during the pre-CNY period vs. 4.11 °C during the CNY week). The spatial distribution of the UHII difference between CNY week and the pre-CNY period is closely related to the locations of functional population zones. UHII for daily maximum temperature decreases most (80%, 0.40 °C during the pre-CNY period vs. 0.08 °C during the CNY period) between the Third and Fourth Ring Roads (RRs), an area which experiences high human activity and has the highest floating population percentage. This study can provide suggestions for optimizing the layout of urban space and land-use structures.</p>

scholarly journals The impact of differences in large-scale circulation output from climate models on the regional modeling of ozone and PM

2012 ◽  
Vol 12 (20) ◽  
pp. 9441-9458 ◽  
Author(s):  
A. M. M. Manders ◽  
E. van Meijgaard ◽  
A. C. Mues ◽  
R. Kranenburg ◽  
L. H. van Ulft ◽  
...  
Keyword(s):  
Air Quality ◽  
Climate Models ◽  
Climate Model ◽  
Transport Model ◽  
Global Climate Model ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Climate Simulations ◽  
The Impact

Abstract. Climate change may have an impact on air quality (ozone, particulate matter) due to the strong dependency of air quality on meteorology. The effect is often studied using a global climate model (GCM) to produce meteorological fields that are subsequently used by chemical transport models. However, climate models themselves are subject to large uncertainties and fail to reproduce the present-day climate adequately. The present study illustrates the impact of these uncertainties on air quality. To this end, output from the SRES-A1B constraint transient runs with two GCMs, i.e. ECHAM5 and MIROC-hires, has been dynamically downscaled with the regional climate model RACMO2 and used to force a constant emission run with the chemistry transport model LOTOS-EUROS in a one-way coupled run covering the period 1970–2060. Results from the two climate simulations have been compared with a RACMO2-LOTOS-EUROS (RLE) simulation forced by the ERA-Interim reanalysis for the period 1989–2009. Both RLE_ECHAM and RLE_MIROC showed considerable deviations from RLE_ERA for daily maximum temperature, precipitation and wind speed. Moreover, sign and magnitude of these deviations depended on the region. The differences in average present-day concentrations between the simulations were equal to (RLE_MIROC) or even larger than (RLE_ECHAM) the differences in concentrations between present-day and future climate (2041–2060). The climate simulations agreed on a future increase in average summer ozone daily maximum concentrations of 5–10 μg m−3 in parts of Southern Europe and a smaller increase in Western and Central Europe. Annual average PM10 concentrations increased 0.5–1.0 μg m−3 in North-West Europe and the Po Valley, but these numbers are rather uncertain: overall, changes for PM10 were small, both positive and negative changes were found, and for many locations the two climate runs did not agree on the sign of the change. This illustrates that results from individual climate runs can at best indicate tendencies and should therefore be interpreted with great care.

scholarly journals Return Levels of Temperature Extremes in Southern Pakistan

2017 ◽  
Author(s):  
Maida Zahid ◽  
Richard Blender ◽  
Valerio Lucarini ◽  
Maria Caterina Bramati
Keyword(s):  
Bias Correction ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Extreme Temperatures ◽  
Return Levels ◽  
Rural And Urban ◽  
The World ◽  
Peak Over Threshold

Abstract. Southern Pakistan (Sindh) is one of the hottest regions in the world and is highly vulnerable to temperature extremes. In order to improve rural and urban planning, information about the recurrence of temperature extremes is required. In this work, return levels of the daily maximum temperature Tmax are estimated, as well as the daily maximum wet-bulb temperature TWmax extremes. The method used is the Peak Over Threshold (POT) and it represents a novelty among the approaches previously used for similar studies in this region. Two main datasets are analyzed: temperatures observed in nine meteorological stations in southern Pakistan from 1980 to 2013, and the ERA Interim data for the nearest corresponding locations. The analysis provides the 2, 5, 10, 25, 50 and 100-year Return Levels (RLs) of temperature extremes. The 90 % quantile is found to be a suitable threshold for all stations. We find that the RLs of the observed Tmax are above 50 °C in northern stations, and above 45 °C in the southern stations. The RLs of the observed TWmax exceed 35 °C in the region, which is considered as a limit of survivability. The RLs estimated from the ERA Interim data are lower by 3 °C to 5 °C than the RLs assessed for the nine meteorological stations. A simple bias correction applied to ERA Interim data improves the RLs remarkably, yet discrepancies are still present. The results have potential implications for the risk assessment of extreme temperatures in Sindh.

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