scholarly journals Variation Characteristics Mathematical Calculation of O3 and Its Relationship with Meteorological Factors by Big Data Technology

2021 ◽  
Vol 2083 (3) ◽  
pp. 032001
Author(s):  
Tiantian Jin ◽  
Lei Wang ◽  
Yuguang Zhao ◽  
Luming Shen
Keyword(s):  
Average Concentration ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Total Solar Radiation ◽  
Ozone Pollution ◽  
Southerly Wind ◽  
Minimum Relative Humidity ◽  
Variation Characteristics ◽  
Meteorological Elements

Abstract Based on the data of environmental monitoring stations and meteorological stations in Qinhuangdao from May 2017 to May 2020, the variation characteristics of O3 and precursors (NO2 and CO) as well as their relationship with meteorological elements were analyzed. The results showed that the daily average concentration of O3-8 h in Qinhuangdao increased year by year. The monthly average concentration of O3-8 h was high in summer and low in winter, and the peak appeared in June. The diurnal variation of O3 concentration was unimodal structure, and the concentration increased in the afternoon, but it decreased at night. The concentration of NO2 and CO was inversely correlated with O3, and the peak value of NO2 in March could be related to frequent cold air activity and increased burning of loose coal. The meteorological elements favorable for the occurrence of ozone pollution weather in Chengde were total solar radiation irradiance greater than 1000W/m2, the daily maximum temperature greater than 33 °C, and the daily minimum relative humidity less than 40% and 65%∽80%, southerly wind or southwest wind.

scholarly journals A typical weather pattern for the ozone pollution events in North China

2019 ◽  
Author(s):  
Cheng Gong ◽  
Hong Liao
Keyword(s):  
North China ◽  
Transport Model ◽  
Lower Troposphere ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Ozone Pollution ◽  
Chemical Production ◽  
Weather Pattern ◽  
Pollution Events

Abstract. Ground-level observations, reanalyzed meteorological fields and a 3-D global chemical and transport model (GEOS-Chem) were applied in this study to investigate ozone (O3) pollution events (OPEs) in North China (36.5° N–40.5° N, 114.5° E–119.5° E) during 2014–2017. Ozone pollution days (OPDs) were defined as days with maximum daily averaged 8-h (MDA8) concentrations over North China larger than 160 μg m−3, and OPEs were defined as periods with 3 or more consecutive OPDs. Observations showed that there were 167 OPDs and 27 OPEs in North China during 2014–2017, in which 123 OPDs and 21 OPEs occurred in May–July. We found that OPEs in North China occurred under a typical weather pattern with high daily maximum temperature (Tmax), low relative humidity (RH), anomalous southerlies and divergence in the lower troposphere, an anomalous high-pressure system at 500 hPa and an anomalous downward air flow from 500 hPa to the surface. Under such a weather pattern, chemical production of O3 was high between 800 and 900 hPa, which was then transported downward to enhance O3 pollution at the surface. A standardized index I_OPE was defined by applying four key meteorological parameters, including Tmax, RH, meridional winds at 850 hPa (V850) and zonal winds at 500 hPa (U500). I_OPE can capture approximately 80 % of the observed OPDs and OPEs, which has implications for forecasting OPEs in North China.

A GAM for Daily Ozone Concentration in Seoul

2005 ◽  
Vol 277-279 ◽  
pp. 497-502 ◽  
Author(s):  
Jae Hee Kim ◽  
Jungmin Hong
Keyword(s):  
Generalized Additive Model ◽  
Additive Model ◽  
Multiple Linear Regression Model ◽  
Environmental Data ◽  
Atmospheric Pollutants ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Ozone Pollution ◽  
Data Dynamics

This study focuses on ozone modeling using meteorological and air monitoring variables. Twenty seven (27) places in Seoul were measured for ozone values from January 1999 to December 1999. Air quality monitoring data consisted of CO, NO2, O3, PM10, TSP while meteorology data consisted of the daily maximum temperature, humidity and wind speed, and solar radiation. The complexity of environmental data dynamics often requires models covering non-linearity. Photochemical ozone pollution is the result of complex non-linear interactions between atmospheric pollutants and meteorology. The generalized additive model is favored because it is the most flexible, has the fewest statistical assumptions, and it can detect and fit potentially complex and nonlinear dependencies. For these reasons we modeled the daily ozone amount using a generalized additive model with smooth loess functions and compared it with a multiple linear regression model.

scholarly journals Temperature, Precipitation, Ozone Pollution, and Daily Fatal Unintentional Injuries in Jiangsu Province, China during 2015-2017

2020 ◽  
Author(s):  
Leon Robertson ◽  
Lian Zhou ◽  
Kai Chen
Keyword(s):  
Unintentional Injury ◽  
Jiangsu Province ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Ozone Pollution ◽  
Injury Death ◽  
Injury Mortality ◽  
Daily Data ◽  
Moderate Range

Abstract Background The correlation of unintentional injury mortality to rising temperatures found in several studies could result from changes in behavior that increases exposure to hazards or risk when exposed. Temperature, precipitation and air pollutants may contribute to symptoms and distractions that increase risk or avoidance behavior that reduces risk. This study examines data that allows estimates of the relation of daily maximum temperature, precipitation and ozone pollution to injury mortality risk, each corrected statistically for the correlation with the others.Methods Daily data on unintentional injury deaths and exposures to temperature, precipitation and ozone in 9 cities in Jiangsu Province, China during 2015-2017 were analyzed using Poisson regression. The regression estimates were adjusted for weekends, holidays, an anomalous difference in death rates in Nanjing, and population size.Results Non transport injury death risk increased substantially in relation to higher temperatures when temperatures were in the moderate range and even more so at temperatures 35 degrees (C) and higher. Transport deaths were related to increasing deaths when temperatures were low but the correlation reversed at higher temperatures. Deaths were lower on rainy days when temperatures were cool and moderate with the exception of non-transport injuries when temperatures were moderate. Higher ozone concentrations were associated with more deaths except when temperatures were low. Injury mortality on weekends and holidays varied in relation to temperature as well. Conclusions The variations in deaths in relation to temperature, precipitation and ozone suggest that people are behaving differently or are in different environments when specific combinations of the predictor variables are prevalent, putting them at greater or less risk. More study of the behaviors and circumstances that result in injury under those conditions is needed.

scholarly journals A typical weather pattern for ozone pollution events in North China

2019 ◽  
Vol 19 (22) ◽  
pp. 13725-13740 ◽  
Author(s):  
Cheng Gong ◽  
Hong Liao
Keyword(s):  
North China ◽  
Transport Model ◽  
Lower Troposphere ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Ozone Pollution ◽  
Chemical Production ◽  
Weather Pattern ◽  
Pollution Events

Abstract. Ground-level observations, reanalyzed meteorological fields and a 3-D global chemical and transport model (GEOS-Chem) were applied in this study to investigate ozone (O3) pollution events (OPEs) in North China (36.5–40.5∘ N, 114.5–119.5∘ E) during 2014–2017. Ozone pollution days (OPDs) were defined as days with maximum daily averaged 8 h (MDA8) concentrations over North China larger than 160 µg m−3, and OPEs were defined as periods with 3 or more consecutive OPDs. Observations showed that there were 167 OPDs and 27 OPEs in North China during 2014–2017, in which 123 OPDs and 21 OPEs occurred from May to July. We found that OPEs in North China occurred under a typical weather pattern with high daily maximum temperature (Tmax), low relative humidity (RH), anomalous southerlies and divergence in the lower troposphere, an anomalous high-pressure system at 500 hPa, and an anomalous downward air flow from 500 hPa to the surface. Under such a weather pattern, chemical production of O3 was high between 800 and 900 hPa, which was then transported downward to enhance O3 pollution at the surface. A standardized index I_OPE was defined by applying four key meteorological parameters, including Tmax, RH, meridional winds at 850 hPa (V850) and zonal winds at 500 hPa (U500). I_OPE can capture approximately 80 % of the observed OPDs and OPEs, which has implications for forecasting OPEs in North China.

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 Joint Occurrence of Daily Temperature and Precipitation Extreme Events over Canada

2014 ◽  
Vol 53 (9) ◽  
pp. 2148-2162 ◽  
Author(s):  
Bárbara Tencer ◽  
Andrew Weaver ◽  
Francis Zwiers
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Negative Consequences ◽  
Temperature And Precipitation ◽  
Joint Occurrence

AbstractThe occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.

scholarly journals Observed Trends in Indices of Daily Temperature Extremes in South America 1960–2000

2005 ◽  
Vol 18 (23) ◽  
pp. 5011-5023 ◽  
Author(s):  
L. A. Vincent ◽  
T. C. Peterson ◽  
V. R. Barros ◽  
M. B. Marino ◽  
M. Rusticucci ◽  
...  
Keyword(s):  
Climate Change ◽  
South America ◽  
Climate Extremes ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Increasing Trends

Abstract A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America.

Assessing the contribution of multiple forcings to changes in temperature extremes 1981–2020 using CMIP6 climate models

2021 ◽  
Author(s):  
Mastawesha Misganaw Engdaw ◽  
Andrew Ballinger ◽  
Gabriele Hegerl ◽  
Andrea Steiner
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Climate Models ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Cold Temperatures

<p>In this study, we aim at quantifying the contribution of different forcings to changes in temperature extremes over 1981–2020 using CMIP6 climate model simulations. We first assess the changes in extreme hot and cold temperatures defined as days below 10% and above 90% of daily minimum temperature (TN10 and TN90) and daily maximum temperature (TX10 and TX90). We compute the change in percentage of extreme days per season for October-March (ONDJFM) and April-September (AMJJAS). Spatial and temporal trends are quantified using multi-model mean of all-forcings simulations. The same indices will be computed from aerosols-, greenhouse gases- and natural-only forcing simulations. The trends estimated from all-forcings simulations are then attributed to different forcings (aerosols-, greenhouse gases-, and natural-only) by considering uncertainties not only in amplitude but also in response patterns of climate models. The new statistical approach to climate change detection and attribution method by Ribes et al. (2017) is used to quantify the contribution of human-induced climate change. Preliminary results of the attribution analysis show that anthropogenic climate change has the largest contribution to the changes in temperature extremes in different regions of the world.</p><p><strong>Keywords:</strong> climate change, temperature, extreme events, attribution, CMIP6</p><p> </p><p><strong>Acknowledgement:</strong> This work was funded by the Austrian Science Fund (FWF) under Research Grant W1256 (Doctoral Programme Climate Change: Uncertainties, Thresholds and Coping Strategies)</p>

Sign in / Sign up

Export Citation Format

Share Document