A Statistical Procedure for Analyzing the Behavior of Air Pollutants during Temperature Extreme Events: The Case Study of Emilia-Romagna Region (Northern Italy)

Meteorological conditions play a crucial role in air pollution by affecting both directly and indirectly the emissions, transport, formation, and deposition of air pollutants. Extreme weather events can strongly affect surface air quality. Understanding relations between air pollutant concentrations and extreme weather events is a fundamental step toward improving the knowledge of how excessive heat impacts on air quality. In this work, we developed a statistical procedure for investigating the variations in the correlation structure of four air pollutants (NOx, O3, PM10, PM2.5) during extreme temperature events measured in monitoring sites located of Emilia Romagna region, Northern Italy, in summer (June–August) from 2015 to 2017. For the selected stations, Hot Days (HDs) and Heat Waves (HWs) were identified with respect to historical series of maximum temperature measured for a 30-year period (1971–2000). This method, based on multivariate techniques, allowed us to highlight the variations in air quality of study area due to the occurrence of HWs. The examined data, including PM concentrations, show higher values, whereas NOx and O3 concentrations seem to be not influenced by HWs. This operative procedure can be easily exported in other geographical areas for studying effects of climate change on a local scale.

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Impact of Extreme Weather Events on Aboveground Net Primary Productivity and Sheep Production in the Magellan Region, Southernmost Chilean Patagonia

Geosciences ◽

10.3390/geosciences10080318 ◽

2020 ◽

Vol 10 (8) ◽

pp. 318

Author(s):

Pamela Soto-Rogel ◽

Juan-Carlos Aravena ◽

Wolfgang Jens-Henrik Meier ◽

Pamela Gross ◽

Claudio Pérez ◽

...

Keyword(s):

Primary Productivity ◽

Net Primary Productivity ◽

Extreme Weather ◽

Extreme Weather Events ◽

Maximum Temperature ◽

Aboveground Net Primary Productivity ◽

Weather Events ◽

Chilean Patagonia ◽

Magellan Region ◽

Sheep Production

Spatio-temporal patterns of climatic variability have effects on the environmental conditions of a given land territory and consequently determine the evolution of its productive activities. One of the most direct ways to evaluate this relationship is to measure the condition of the vegetation cover and land-use information. In southernmost South America there is a limited number of long-term studies on these matters, an incomplete network of weather stations and almost no database on ecosystems productivity. In the present work, we characterized the climate variability of the Magellan Region, southernmost Chilean Patagonia, for the last 34 years, studying key variables associated with one of its main economic sectors, sheep production, and evaluating the effect of extreme weather events on ecosystem productivity and sheep production. Our results show a marked multi-decadal character of the climatic variables, with a trend to more arid conditions for the last 8 years, together with an increase in the frequency of extreme weather events. Significant percentages of aboveground net primary productivity (ANPP) variance is explained by high precipitation, mesic temperatures, and low evapotranspiration. These conditions are, however, spatially distributed in the transition zone between deciduous forests and steppe and do not represent a general pattern for the entire region. Strong precipitation and wind velocity negatively affect lamb survival, while temperature and ANPP are positively correlated. The impact of extreme weather events on ANP and sheep production (SP) was in most of the cases significantly negative, with the exception of maximum temperature that correlated with an increase of ANPP, and droughts that showed a non-significant negative trend in ANPP. The examination of these relationships is urgent under the current scenario of climate change with the acceleration of the environmental trends here detected.

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Determining the Effect of Extreme Weather Events on Human Participation in Recreation and Tourism: A Case Study of the Toronto Zoo

Atmosphere ◽

10.3390/atmos11010099 ◽

2020 ◽

Vol 11 (1) ◽

pp. 99

Author(s):

Micah Hewer

Keyword(s):

Extreme Weather ◽

Extreme Weather Events ◽

Maximum Temperature ◽

Distance Method ◽

Daily Weather ◽

Weather Events ◽

Daily Weather Data ◽

Weather Stations ◽

Recreation And Tourism

This study devises a novel approach for defining extreme weather events and assessing their effects on human participation in recreation and tourism, based on a case study of attendance at the Toronto Zoo (Toronto, ON, Canada). Daily zoo attendance data from 1999 to 2018 was obtained and analyzed in connection with daily weather data from local weather stations for the maximum temperature, minimum temperature, total precipitation, and maximum wind speed. The “climatic distance” method, used for evaluating representative weather stations for case studies in applied climatology, was employed to rank and select surrounding weather stations that most accurately captured daily weather observations recorded at the Toronto Zoo from 1990 to 1992. Extreme weather events can be defined as lying in the outermost (most unusual) 10 percent of a place’s history. Using this definition as the foundation, a percentile approach was developed to identify and assess the effects of extreme weather events across the following thresholds: the 99th percentile, the 95th percentile, and the 90th percentile, as well as less than the 1st percentile, less than the 5th percentile, and less than the 10th percentile. Additionally, revealed, theoretical, and binary thresholds were also assessed to verify their merit and determine their effects, and were compared to the extreme weather events defined by the percentiles approach. Overall, extreme daily weather events had statistically significant negative effects on zoo attendance in Toronto, apart from a few cases, such as the positive effect of usually warm daytime temperatures in the winter and usually cool nighttime temperatures in the summer. The most influential weather event across all seasons was extremely hot temperatures, which has important implications for climate change impact assessments.

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Emergence of projected scaled patterns of extreme weather events over Europe

10.5194/egusphere-egu21-14082 ◽

2021 ◽

Author(s):

Tugba Ozturk ◽

Dominic Matte ◽

Jens Hesselbjerg Christensen

Keyword(s):

Hot Spot ◽

Regional Climate ◽

Extreme Weather ◽

Extreme Weather Events ◽

Maximum Temperature ◽

Climate Projections ◽

Global Mean Temperature ◽

Temperature And Precipitation ◽

Weather Events ◽

Simple Scaling

<div><span>In this work, we investigate the scalability of wet and dry persisting conditions over the European domain. For this aim, we have used the EURO-CORDEX ensemble of regional climate projections at 0.11&#176; grid-mesh for daily minimum and maximum temperature and precipitation to analyze future changes in relation with extreme weather events addressing climate warming targets of 1&#176;C, 2&#176;C and 3&#176;C, respectively. A simple scaling with the annual mean global mean temperature change modeled by the driving GCM is applied. We also identify the emergence of the scaled patterns of minimum and maximum temperatures and of wet and dry persisting conditions in relation with certain extreme weather indices. In particular we focus on pattern scaling of extreme temperatures and precipitation over sub-regions over the Mediterranean basin since this region has been identified as a climate change hot spot.</span></div>

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Overview of Injuries Associated with Extreme Weather Events in New Hampshire, U.S., 2001–2009

Atmosphere ◽

10.3390/atmos11030281 ◽

2020 ◽

Vol 11 (3) ◽

pp. 281

Author(s):

Kelly Neugent ◽

Kathleen F. Bush ◽

Eric Kelsey ◽

Matthew Cahillane ◽

Eric Laflamme

Keyword(s):

Public Health ◽

New Hampshire ◽

Daily Precipitation ◽

Extreme Weather ◽

Extreme Weather Events ◽

Maximum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Weather Events ◽

Hospital Visits

Global climate change is an environmental hazard with significant public health impacts. High-impact weather events including periods of extreme temperature or extreme precipitation are frequently associated with adverse effects on human health. This study evaluates the impact of extreme weather events on injuries across New Hampshire. A set of five daily extreme weather metrics (EWMs) was analyzed: daily maximum temperature ≤32 °F (0 °C), daily maximum temperature ≥90 °F (32 °C), daily maximum temperature ≥95 °F (35 °C), daily precipitation ≥1″, and daily precipitation ≥2″. Exposure to these EWMs was defined by linking the population within 10 miles of nine weather stations distributed across the state. Injuries were defined as hospitalizations categorized as: all-cause injury, vehicle accidents, accidental falls, accidents due to natural and environmental causes (including excessive heat, excessive cold, exposure due to weather conditions, lightning, and storms and floods), accidental drowning, and carbon monoxide poisoning. The associations between all injury categories and all EWMs as well as daily maximum temperature and daily precipitation were explored. A quasi-Poisson regression model was used to evaluate the relationship between the four strongest exposure–outcome pairs linking maximum temperature to all-cause injury-, vehicle accident-, accidental fall-, and heat-related hospital visits. Results indicate that daily maximum temperature (>90 °F) was most strongly associated with heat-related hospital visits and was also associated with all-cause injury-related hospital visits. Future work should include further analysis of cold weather metrics and incorporate these findings into public health planning and response efforts.

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