scholarly journals Spatio-Temporal Correlation Analysis of Air Quality in China: Evidence from Provincial Capitals Data

2020 ◽  
Vol 12 (6) ◽  
pp. 2486
Author(s):  
Qingchen Liu ◽  
Xinyi Li ◽  
Tao Liu ◽  
Xiaojun Zhao
Keyword(s):  
Air Quality ◽  
Temporal Correlation ◽  
Temporal Analysis ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Capital Cities ◽  
Temporal Correlations ◽  
Agglomeration Effects ◽  
Provincial Capital ◽  
Spatio Temporal

In China, public health awareness is growing as people get more concerned about the air quality. Based on the air quality index (AQI) of 31 provincial capital cities (2015–2018) in China, we studied the spatio-temporal correlations of air quality between cities. With spatial, temporal and spatio-temporal analysis, we systematically obtained many interesting results where the traditional analyses may be lacking. Firstly, the air quality of cities has spatial spillover and agglomeration effects and further the spatial correlation becomes higher with time. Secondly, there exists temporal correlation between the current AQI and its past values on multiple time scales, which shows certain periodicity. Thirdly, due to the changing characteristics of time, social activities and other factors affect the air quality positively. However, with the panel data model, the coefficients of spatio-temporal correlation vary for different cities.

scholarly journals Spatio-temporal analysis of air quality and its relationship with major COVID-19 hotspot places in India

2021 ◽  
Vol 22 ◽  
pp. 100473
Author(s):  
Hasan Raja Naqvi ◽  
Guneet Mutreja ◽  
Adnan Shakeel ◽  
Masood Ahsan Siddiqui
Keyword(s):  
Air Quality ◽  
Temporal Analysis ◽  
Spatio Temporal

scholarly journals Changes in speciated PM2.5 concentrations in Fresno, California, due to NOx reductions and variations in diurnal emission profiles by day of week

Elem Sci Anth ◽  
2019 ◽  
Vol 7 ◽  
Author(s):  
Benjamin de Foy ◽  
James J. Schauer
Keyword(s):  
Air Quality ◽  
Organic Carbon ◽  
Ammonium Nitrate ◽  
Forest Fires ◽  
Multiple Linear Regression Model ◽  
Time Of Day ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Wood Combustion ◽  
Carbon Concentrations

The San Joaquin Valley in California suffers from poor air quality due to a combination of local emissions and weak ventilation. Over the course of decades, there has been a concerted effort to control emissions from vehicles as well as from residential wood burning. A multiple linear regression model was used to evaluate the trends in air pollution over multiple time scales: by year, by season, by day of the week and by time of day. The model was applied to 18 years of measurements in Fresno including hourly mole fractions of NOx and concentrations of PM2.5; and daily measurements of speciated components of PM2.5. The analysis shows that there have been reductions in NOx, elemental carbon and ammonium nitrate of 4 to 6%/year. On weekends, NOx mole fractions are reduced by 15 to 30% due to fewer vehicle miles traveled and a smaller fraction of diesel traffic. These weekend reductions in NOx have not been accompanied by weekend reductions in PM2.5 however. In particular, elemental and organic carbon concentrations are higher on winter weekends. Analysis of diurnal profiles suggests that this is because of increased PM2.5 on Saturday and holiday evenings which are likely due to residential wood combustion. Furthermore, while organic carbon concentrations have decreased in the winter months, they have been variable but without a net decline in the summer, most likely as a result of forest fires offsetting other improvements in air quality. Fog was found to greatly enhance ammonium nitrate formation and was therefore associated with higher PM2.5 in the winter months. Overall the analysis shows that air quality controls have been effective at reducing NOx all year and PM2.5 in the winter, that continued reductions in emissions will further reduce pollutant concentrations, but that winter residential wood combustion and summer forest fires could offset some of the gains obtained.

Comparison of Early Cortical Networks in Efficient and Inefficient Visual Search: An Event-Related Potential Study

2003 ◽  
Vol 15 (7) ◽  
pp. 1039-1051 ◽  
Author(s):  
Ute Leonards ◽  
Julie Palix ◽  
Christoph Michel ◽  
Vicente Ibanez
Keyword(s):  
Event Related Potentials ◽  
Temporal Correlation ◽  
Temporal Analysis ◽  
Search Display ◽  
Stimulus Onset ◽  
Event Related Potential ◽  
Time Range ◽  
Cortical Networks ◽  
Related Potentials ◽  
Spatio Temporal

Functional magnetic resonance imaging studies have indicated that efficient feature search (FS) and inefficient conjunction search (CS) activate partially distinct frontoparietal cortical networks. However, it remains a matter of debate whether the differences in these networks reflect differences in the early processing during FS and CS. In addition, the relationship between the differences in the networks and spatial shifts of attention also remains unknown. We examined these issues by applying a spatio-temporal analysis method to high-resolution visual event-related potentials (ERPs) and investigated how spatio-temporal activation patterns differ for FS and CS tasks. Within the first 450 msec after stimulus onset, scalp potential distributions (ERP maps) revealed 7 different electric field configurations for each search task. Configuration changes occurred simultaneously in the two tasks, suggesting that contributing processes were not significantly delayed in one task compared to the other. Despite this high spatial and temporal correlation, two ERP maps (120–190 and 250–300 msec) differed between the FS and CS. Lateralized distributions were observed only in the ERP map at 250–300 msec for the FS. This distribution corresponds to that previously described as the N2pc component (a negativity in the time range of the N2 complex over posterior electrodes of the hemisphere contralateral to the target hemifield), which has been associated with the focusing of attention onto potential target items in the search display. Thus, our results indicate that the cortical networks involved in feature and conjunction searching partially differ as early as 120 msec after stimulus onset and that the differences between the networks employed during the early stages of FS and CS are not necessarily caused by spatial attention shifts.

scholarly journals Improved Spatio-Temporal Residual Networks for Bus Traffic Flow Prediction

2019 ◽  
Vol 9 (4) ◽  
pp. 615 ◽  
Author(s):  
Panbiao Liu ◽  
Yong Zhang ◽  
Dehui Kong ◽  
Baocai Yin
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Transportation Network ◽  
Temporal Correlation ◽  
Traffic Flow Prediction ◽  
Temporal Correlations ◽  
Building Models ◽  
Spatio Temporal ◽  
Specific Scenario

Buses, as the most commonly used public transport, play a significant role in cities. Predicting bus traffic flow cannot only build an efficient and safe transportation network but also improve the current situation of road traffic congestion, which is very important for urban development. However, bus traffic flow has complex spatial and temporal correlations, as well as specific scenario patterns compared with other modes of transportation, which is one of the biggest challenges when building models to predict bus traffic flow. In this study, we explore bus traffic flow and its specific scenario patterns, then we build improved spatio-temporal residual networks to predict bus traffic flow, which uses fully connected neural networks to capture the bus scenario patterns and improved residual networks to capture the bus traffic flow spatio-temporal correlation. Experiments on Beijing transportation smart card data demonstrate that our method achieves better results than the four baseline methods.

ESTIMATION OF CONVECTION SPEED THROUGH PIV MEASUREMENTS IN TURBULENT PLANAR MIXING LAYER

2009 ◽  
Vol 23 (03) ◽  
pp. 353-356
Author(s):  
CHIUAN-TING LI ◽  
KEH-CHIN CHANG ◽  
MUH-RONG WANG
Keyword(s):  
Particle Image ◽  
Mixing Layer ◽  
Temporal Correlation ◽  
Dominant Frequency ◽  
Piv Measurements ◽  
Temporal Correlations ◽  
Taylor’S Hypothesis ◽  
Image Velocimetry ◽  
Spatio Temporal ◽  
Convection Speed

The spatio-temporal correlations in a turbulent planar mixing layer are acquired using the particle image velocimetry. Estimation of convection speed is recommended to be made with the spatio-temporal correlations of fluctuating vorticity. The spatial correlation can be deduced from the temporal correlation through the use of the Taylor's hypothesis when applied to the region without apparent dominant frequency.

scholarly journals Changes of air quality and its associated health and economic burden in 31 provincial capital cities in China during COVID-19 pandemic

2021 ◽  
Vol 249 ◽  
pp. 105328 ◽  
Author(s):  
Dongyang Nie ◽  
Fuzhen Shen ◽  
Junfeng Wang ◽  
Xiaoyun Ma ◽  
Zhirao Li ◽  
...  
Keyword(s):  
Air Quality ◽  
Economic Burden ◽  
Capital Cities ◽  
Provincial Capital

scholarly journals Long-Term Atmospheric Visibility Trends and Characteristics of 31 Provincial Capital Cities in China during 1957–2016

Atmosphere ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 318 ◽  
Author(s):  
Weicong Fu ◽  
Ziru Chen ◽  
Zhipeng Zhu ◽  
Qunyue Liu ◽  
Jinda Qi ◽  
...  
Keyword(s):  
Air Quality ◽  
Socioeconomic Factors ◽  
Urban Areas ◽  
Meteorological Factors ◽  
Ambient Air ◽  
Ambient Air Quality ◽  
Capital Cities ◽  
The Public ◽  
Provincial Capital

Millions of pulmonary diseases, respiratory diseases, and premature deaths are caused by poor ambient air quality in developing countries, especially in China. A proven indicator of ambient air quality, atmospheric visibility (AV), has displayed continuous decline in China’s urban areas. A better understanding of the characteristics and the factors affecting AV can help the public and policy makers manage their life and work. In this study, long-term AV trends (from 1957–2016, excluding 1965–1972) and spatial characteristics of 31 provincial capital cities (PCCs) of China (excluding Taipei, Hong Kong, and Macau) were investigated. Seasonal and annual mean values of AV, percentage of ‘good’ (≥20 km) and ‘bad’ AV (<10 km), cumulative percentiles and the correlation between AV, socioeconomic factors, air pollutants and meteorological factors were analyzed in this study. Results showed that annual mean AV of the 31 PCCs in China were 14.30 km, with a declining rate of −1.07 km/decade. The AV of the 31 PCCs declined dramatically between 1973–1986, then plateaued between 1987–2006, and rebounded slightly after 2007. Correlation analysis showed that impact factors (e.g., urban size, industrial activities, residents’ activities, urban greening, air quality, and meteorological factors) contributed to the variation of AV. We also reveal that residents’ activities are the primary direct socioeconomic factors on AV. This study hopes to help the public fully understand the characteristics of AV and make recommendations about improving the air environment in China’s urban areas.

Different Circadian Rest-Active Rhythms in Kleine-Levin Syndrome: A prospective and case-control study

SLEEP ◽  
2021 ◽  
Author(s):  
Chen Lin ◽  
Wei-Chih Chin ◽  
Yu-Shu Huang ◽  
Kuo-Chung Chu ◽  
Teresa Paiva ◽  
...  
Keyword(s):  
Circadian Rhythm ◽  
Young Patients ◽  
Recovery Phase ◽  
Multiple Time Scales ◽  
Fluctuation Analysis ◽  
Multiple Time ◽  
Temporal Correlations ◽  
Significant Difference ◽  
Attack Phase ◽  
Physiological Markers

Abstract Study objectives Kleine-Levin-syndrome (KLS) is a rare recurrent hypersomnia. Our study aimed at monitoring the movements of patients with KLS using actigraphy and evaluating their circadian rhythm. Methods Twenty young patients with KLS and 14 age-matched controls were recruited. Each individual wore an actigraphy for more than 6 months to monitor at least two attacks. Controls kept wearing the device for at least 7 days. The activity counts were averaged in hourly basis and the day-to-night amplitude was quantified by the differences of the averaged activity counts during daytime and nighttime. The hourly activities of different days were aligned and averaged to construct the circadian profile. Parametric and nonparametric estimation of circadian rhythm was calculated. We applied detrended fluctuation analysis to evaluate the temporal correlations beneath the activity fluctuations at multiple time scales. Results Circadian rhythm in asymptomatic period showed no significant difference compared to the controls. During hypersomnia attack, the amplitude of the circadian rest-active rhythms drastically decreased and decreased inter-daily stability (IS) was found, as well as significant decreased M10 and short-time fractal correlation (α1). Drastically decreased mean and standard deviation of activity were noted, compared to the pre-attack phase and recovery phase.α1 and M10 increased during the late attack phase, and overcompensated IS was noted in the recovery phase. Conclusions This study confirmed that circadian rest-active rhythms was affected when KLS hypersomnia attack. Several parameters including M10, IS and α1 may be physiological markers of KLS, which can help to predict the end of hypersomnia episodes.

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