Early Warning System and Adaptation Advice to Reduce Human Health Consequences of Extreme Weather Conditions and Air Pollution

2015 ◽  
pp. 265-301 ◽  
Author(s):  
Dragan Bogdanović ◽  
Konstansa Lazarević
Keyword(s):  
Air Pollution ◽  
General Population ◽  
Information Service ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Internet Service ◽  
Wind Chill ◽  
The Republic ◽  
Index Value ◽  
Sensitive Population

The authors developed a multi-site Internet service to provide the public with real time information about local weather and air quality, how they may affect health, and how general population and different sensitive population groups can protect their health during periods of extreme weather conditions or increased air pollution levels. The information service is based on data obtained from the Republic Hydrometeorological Service of Serbia and Serbian Environment Protection Agency. Health warnings and recommendations are given separately for each AIQ and heat index or wind chill index value, for each sensitive population group, as well as for the general population. The project is currently implemented on the website of the Institute of Occupational Health Niš and will be offered to other healthcare institutions in Serbia. Evaluation of the system should enable redefinition of heat and wind chill indices and air pollution threshold values if necessary. This chapter explores the service.

Early Warning System and Adaptation Advice to Reduce Human Health Consequences of Extreme Weather Conditions and Air Pollution

2016 ◽  
pp. 527-564 ◽  
Author(s):  
Dragan Bogdanović ◽  
Konstansa Lazarević
Keyword(s):  
Air Pollution ◽  
General Population ◽  
Information Service ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Internet Service ◽  
Wind Chill ◽  
The Republic ◽  
Index Value ◽  
Sensitive Population

The authors developed a multi-site Internet service to provide the public with real time information about local weather and air quality, how they may affect health, and how general population and different sensitive population groups can protect their health during periods of extreme weather conditions or increased air pollution levels. The information service is based on data obtained from the Republic Hydrometeorological Service of Serbia and Serbian Environment Protection Agency. Health warnings and recommendations are given separately for each AIQ and heat index or wind chill index value, for each sensitive population group, as well as for the general population. The project is currently implemented on the website of the Institute of Occupational Health Niš and will be offered to other healthcare institutions in Serbia. Evaluation of the system should enable redefinition of heat and wind chill indices and air pollution threshold values if necessary. This chapter explores the service.

scholarly journals Effects of COVID-Induced Mobility Restrictions and Weather Conditions on Air Quality in Hungary

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 561
Author(s):  
Adrienn Varga-Balogh ◽  
Ádám Leelőssy ◽  
Róbert Mészáros
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Spatial Heterogeneity ◽  
Emission Reduction ◽  
Road Traffic ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Traffic Regulation ◽  
Traffic Reduction ◽  
Quality Response

Similarly to other countries, the first wave of the COVID pandemic induced a collapse of mobility in Hungary during the spring of 2020. From the environmental perspective, the obtained road traffic reduction of 20–50% could be regarded as an undesired traffic regulation experiment. Air quality impacts within Hungary were evaluated based on data from 52 monitoring sites measuring concentrations of pollutants NOx, O3, and PM10. Air pollution during the lockdown was compared to the same period (February–June) in the reference years 2014–2019. The large spatial heterogeneity of the air quality response was explored. The emission reduction coincided with the extreme weather of 2020, characterized by unusually warm pre-lockdown February and spring drought. The anomalously low pre-lockdown air pollution was further reduced (NOx) or increased (PM10) during the restrictions. Compared to the previous years, NOx concentrations during the curfew were found to differ between −4.1 and +0.2 standard deviations (median −1.55 SD), or −45% and +3% (median −18%) among different monitoring locations. Ozone concentrations were unusually high due to both weather and chemical reasons (median +11% or +0.8 SD), while the PM10 response was modest and largely weather-driven (median +7% or +0.4 SD).

AWARENESS ABOUT INDOOR AIR POLLUTION IN GENERAL POPULATION OF RAWALPINDI AND ISLAMABAD

2018 ◽  
Vol 8 (2) ◽  
pp. 80-83
Author(s):  
Nadia Tariq ◽  
Tamkeen Jaffry ◽  
Rahma Fiaz ◽  
Abdul Majid Rajput ◽  
Sadaf Khalid
Keyword(s):  
Air Pollution ◽  
General Population ◽  
Indoor Air ◽  
Indoor Air Pollution ◽  
Economic Status ◽  
Educational Status ◽  
Epidemiological Studies ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Significant Difference

Background: Indoor air pollutants are increasingly being associated with respiratory illnesses leading to high degree of morbidity and mortality. There are not sufficient epidemiological studies from Pakistan which assess level of awareness of indoor air pollution resulting in respiratory diseases in population. Methods: This cross sectional survey was carried out on general population of Rawalpindi/Islamabad. Sample size was 223 study subjects selected by non-probability convenient sampling. Knowledge of the study subjects was determined with regard to indoor air pollution, its effects on health and different sources of indoor air pollution with the help of a questionnaire. The influence of age, gender, educational status and socio economic status on the level of awareness was also analyzed. Results: Out of total 223 participants, 115 were males and108 females. Participants aware of indoor air pollution were 91.5% and adequate awareness about its sources was 80.7%. Those who knew indoor air pollution is detrimental to health were 95.1%. Awareness about building construction dust as source of indoor air pollution was maximum (84.8%). There was significant difference in awareness among participants with different monthly incomes and educational status and also between males and females. Conclusion: This study concludes that general population of Rawalpindi/Islamabad has fairly good awareness about sources of indoor air pollution. Use of harmful material causing indoor air pollution should be limited or substituted with better ones where possible.

Irrigation regime and water consumption of potatoes in the Republic of Bashkortostan, depending on the reclamation condition of lands

2020 ◽  
Vol 0 (6) ◽  
pp. 13-19
Author(s):  
Guzel Gumerova ◽  
Georgiy Gulyuk ◽  
Dmitry Kucher ◽  
Anatoly Shuravilin ◽  
Elena Piven
Keyword(s):  
Water Consumption ◽  
Weather Conditions ◽  
Growing Season ◽  
Vegetation Period ◽  
Forest Steppe ◽  
Total Water ◽  
Total Water Consumption ◽  
Republic Of Bashkortostan ◽  
Irrigated Lands ◽  
The Republic

Data of long-term researches (2015–2018) in southern forest-steppe zone of the Republic of Bashkortostan, is justified theoretically and experimentally the mode of irrigation of potatoes on leached chernozems of unsatisfactory, satisfactory and good ameliorative condition of irrigated lands. For the growing periods of potatoes with different heat and moisture supply, the number of watering, the timing of their implementation, irrigation and irrigation norms are established. On lands with unsatisfactory meliorative state the number of irrigation depending on weather conditions of potato vegetation period varied from 0 to 3 (1.5 on average) with average irrigation norm – 990 m3/ha. With satisfactory meliorative state of lands the number of irrigation on average increased from 0 to 4 (2.3 on average) with irrigation norm – 1305 m3/ha. On lands with good meliorative state the number of irrigation was the highest – from 1 to 5 (3 on average) with average irrigation irrigation norm is 1653 m3/ha. It was noted that in the dry periods of potato vegetation the greatest number of watering was carried out (3–5 watering), and in the wet periods (2017) watering was not carried out except for the area with a good reclamation state, where only one irrigation was carried out by the norm of 550 m3/ha. Water consumption of potato was studied in dynamics as a whole during the growing season and the months of the growing season depending on weather conditions of vegetation period and land reclamation condition of irrigated lands, as well as in the control (without irrigation). The lowest total water consumption was in the area without irrigation and averaged 226.8 mm. In irrigated areas, its values increased to 319-353.4 mm. The average daily water consumption varied from 2.12 to 3.3 mm. The highest rates of potato water consumption were observed in June and July, and the lowest – in May and August. In the total water consumption of potatoes on the site without irrigation, the largest share was occupied by atmospheric precipitation and in addition to them the arrival of moisture from the soil. Irrigation water was used in irrigated areas along with precipitation, the share of which was 30.2–46.1 %.

scholarly journals Precipitation Modeling for Extreme Weather Based on Sparse Hybrid Machine Learning and Markov Chain Random Field in a Multi-Scale Subspace

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1241
Author(s):  
Ming-Hsi Lee ◽  
Yenming J. Chen
Keyword(s):  
Machine Learning ◽  
Markov Chain ◽  
Random Field ◽  
Long Range ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Prediction Algorithm ◽  
Learning Method ◽  
Multi Scale ◽  
Hybrid Machine

This paper proposes to apply a Markov chain random field conditioning method with a hybrid machine learning method to provide long-range precipitation predictions under increasingly extreme weather conditions. Existing precipitation models are limited in time-span, and long-range simulations cannot predict rainfall distribution for a specific year. This paper proposes a hybrid (ensemble) learning method to perform forecasting on a multi-scaled, conditioned functional time series over a sparse l1 space. Therefore, on the basis of this method, a long-range prediction algorithm is developed for applications, such as agriculture or construction works. Our findings show that the conditioning method and multi-scale decomposition in the parse space l1 are proved useful in resisting statistical variation due to increasingly extreme weather conditions. Because the predictions are year-specific, we verify our prediction accuracy for the year we are interested in, but not for other years.

Multi-objective resilience enhancement program in smart grids during extreme weather conditions

2021 ◽  
Vol 129 ◽  
pp. 106824
Author(s):  
Rahman Ashrafi ◽  
Meysam Amirahmadi ◽  
Mohammad Tolou-Askari ◽  
Vahid Ghods
Keyword(s):  
Smart Grids ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Multi Objective

scholarly journals Extreme weather conditions and dengue outbreak in Guangdong, China: spatial heterogeneity based on climate variability

2021 ◽  
pp. 110900
Author(s):  
Jian Cheng ◽  
Hilary Bambrick ◽  
Laith Yakob ◽  
Gregor Devine ◽  
Francesca D. Frentiu ◽  
...  
Keyword(s):  
Climate Variability ◽  
Spatial Heterogeneity ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Dengue Outbreak

scholarly journals Overheating Risk and Energy Demand of Nordic Old and New Apartment Buildings during Average and Extreme Weather Conditions under a Changing Climate

2021 ◽  
Vol 11 (9) ◽  
pp. 3972
Author(s):  
Azin Velashjerdi Farahani ◽  
Juha Jokisalo ◽  
Natalia Korhonen ◽  
Kirsti Jylhä ◽  
Kimmo Ruosteenoja ◽  
...  
Keyword(s):  
Climate Change ◽  
Energy Demand ◽  
Energy Use ◽  
Residential Buildings ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Living Room ◽  
Extra Energy ◽  
Cooling Unit ◽  
Indoor Conditions

The global average air temperature is increasing as a manifestation of climate change and more intense and frequent heatwaves are expected to be associated with this rise worldwide, including northern Europe. Summertime indoor conditions in residential buildings and the health of occupants are influenced by climate change, particularly if no mechanical cooling is used. The energy use of buildings contributes to climate change through greenhouse gas emissions. It is, therefore, necessary to analyze the effects of climate change on the overheating risk and energy demand of residential buildings and to assess the efficiency of various measures to alleviate the overheating. In this study, simulations of dynamic energy and indoor conditions in a new and an old apartment building are performed using two climate scenarios for southern Finland, one for average and the other for extreme weather conditions in 2050. The evaluated measures against overheating included orientations, blinds, site shading, window properties, openable windows, the split cooling unit, and the ventilation cooling and ventilation boost. In both buildings, the overheating risk is high in the current and projected future average climate and, in particular, during exceptionally hot summers. The indoor conditions are occasionally even injurious for the health of occupants. The openable windows and ventilation cooling with ventilation boost were effective in improving the indoor conditions, during both current and future average and extreme weather conditions. However, the split cooling unit installed in the living room was the only studied solution able to completely prevent overheating in all the spaces with a fairly small amount of extra energy usage.

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