scholarly journals Short-term variation in air quality associated with firework events: A case study

2003 ◽  
Vol 5 (2) ◽  
pp. 260-264 ◽  
Author(s):  
Khaiwal Ravindra ◽  
Suman Mor ◽  
C. P. Kaushik
Keyword(s):  
Air Quality ◽  
Short Term ◽  
Term Variation

scholarly journals Air Quality in Six Northern Indian Cities During Diwali 2020: The Real Tragedy in Disguise

2021 ◽  
Vol 33 (4) ◽  
pp. 909-918
Author(s):  
A.J. Lawrence ◽  
A. Abraham ◽  
F. Ali ◽  
S. Arif ◽  
S. Fatima ◽  
...  
Keyword(s):  
Air Quality ◽  
Negative Relationship ◽  
Short Term ◽  
Positive Correlation ◽  
The Real ◽  
Term Variation ◽  
Diwali Festival ◽  
The Government ◽  
Indian Cities ◽  
Quality Variation

North Indian cities have been highly polluted, especially in winters, which coincide with the Diwali festival. This year, the government imposed ban on the burning of firecrackers. This study was undertaken from 4th-21st November, 2020 to monitor the air quality variation with respect to PM10 and PM2.5 for Delhi, Lucknow, Ghaziabad, Muzaffarnagar, Greater Noida and Bulandshahar cities during and post Diwali period, to know whether there was any impact of the warnings. The hourly variations in the AQI were very poor between 8:00 p.m.-10:00 p.m. on Diwali day. Significant short term variation in the AQI was observed during the night. A weak positive correlation was obtained between the temperature and AQI, whereas a negative relationship was established with humidity. As compared to last year’s AQI, higher values were obtained this year. The short-term variation in air quality may prove crucial in future in the wake of COVID-19 pandemic.

scholarly journals Associativity Analysis of SO<sub>2</sub> and NO<sub>2</sub> for Alberta Monitoring Data Using KZ Filtering and Hierarchical Clustering

2018 ◽  
Author(s):  
Joana Soares ◽  
Paul Andrew Makar ◽  
Yayne-abeba Aklilu ◽  
Ayodeji Akingunola
Keyword(s):  
Time Series ◽  
Air Quality ◽  
Hierarchical Clustering ◽  
Euclidean Distance ◽  
Monitoring Network ◽  
Air Quality Model ◽  
Quality Model ◽  
Short Term ◽  
Monitoring Network Design ◽  
Term Variation

Abstract. Abstract. Associativity analysis is a powerful tool to deal with large-scale datasets by clustering the data on the basis of (dis)similarity, and can be used to assess the efficacy and design of air-quality monitoring networks. We describe here our use of Kolmogorov-Zurbenko filtering and hierarchical clustering of NO2 and SO2 passive and continuous monitoring data, to analyse and optimize air quality networks for these species in the province of Alberta, Canada. The methodology applied in this study assesses dissimilarity between monitoring station time series based on two metrics: 1-R, R being the Pearson correlation coefficient, and the Euclidean distance. We have combined the analytic power of hierarchical clustering with the spatial information provided by deterministic air quality model results, using the gridded time series of model output as potential station locations, as a proxy for assessing monitoring network design and for network optimization. We find that both metrics should be used to evaluate the similarity between monitoring time series, since this allows a cross-comparison in terms of temporal variation and magnitude of concentrations to assess station potential redundancy. Here, the relative level of potential redundancy of an existing monitoring location was ranked according to each dissimilarity metric, with sites forming clusters at low values of both 1-R and Euclidean distance being the most redundant. We demonstrate clustering results depend on the air contaminant analyzed, reflecting the difference in the respective emission sources of SO2 and NO2 in the region under study. Our work shows that much of the signal identifying the sources of NO2 and SO2 emissions resides in shorter time scales (hourly to daily) due to short-term variation of concentrations. However, the methodology nevertheless identifies stations mainly influenced by seasonality, if larger time scales (weekly to monthly) are considered. We have found that data consisting of longer-term averages may lose the short-term variation needed to identify local sources, implying that long-term averaged observations are not suitable for source identification purposes. In addition to averaging time, round-off levels in data reports, and the accuracy of instrumentation were also shown to have a negative influence on the clustering results. We have performed the first dissimilarity analysis based on gridded air-quality model output, and have shown that the methodology is capable of generating maps of sub-regions within which a single station will represent the entire sub-region, to a given level of dissimilarity. Maps of this nature may be combined with other georeferenced data (e.g. road networks, power availability) to assist in monitoring network design. We have also shown that our methodology is capable of identifying different sampling methodologies, as well as identifying outliers (stations’ time series which are markedly different from all others in a given dataset).

scholarly journals The Impact of a Building Implosion on Ambient Air Quality: A Case Study in an Urban Coastal City

2021 ◽  
pp. 1-7
Author(s):  
Bindu G ◽  
◽  
Anju Farhana C ◽  
Keyword(s):  
Air Quality ◽  
Ambient Air ◽  
Permissible Limit ◽  
Ambient Air Quality ◽  
Short Term ◽  
Coastal City ◽  
Permissible Limits ◽  
Pm10 And Pm2.5 ◽  
The Impact

This study was carried out to assess the impact of implosion of four multi-storied apartments in an urban coastal city, Kochi, India on the ambient air quality. Air quality monitoring was conducted pre and post demolition stages indicated that there was short-term air quality deterioration surrounding the demolition sites. The increase of SPM, PM10 and PM2.5 was above the permissible limits during demolition which reduced afterwards, but was above the ambient level monitored in the pre demolition stage. In the case of SPM the concentration increased to 3004µgm/m3 during implosion in one of the sites, Golden Kayaloram. This site showed PM10 and PM2.5 also to be above permissible limits during implosion. This is followed by the monitoring sites of Jain Coral Cove, which also showed higher concentration levels above permissible limit during demolition. Other apartments, Alfa Serene and Holyfaith share the same monitoring sites and exceeds permissible limit for SPM and PM2.5 during demolition. In general more sites reported concentration above permissible limits for PM2.5. The average air quality after three months of implosion shows that, the pollutant concentration was much higher than the pre-demolition level. These results clearly show that building implosion is having severe impact on local air quality

scholarly journals Particulate Matter Short-Term Exposition, Mobility Trips and COVID-19 Diffusion: A Correlation Analyses for the Italian Case Study at Urban Scale

2021 ◽  
Vol 13 (8) ◽  
pp. 4553
Author(s):  
Armando Cartenì ◽  
Furio Cascetta ◽  
Luigi Di Francesco ◽  
Felisia Palermo
Keyword(s):  
Air Quality ◽  
Prolonged Exposure ◽  
Term Effect ◽  
Short Term ◽  
Italian Case ◽  
Correlation Analyses ◽  
Global Pandemic ◽  
Outdoor Environments ◽  
Definition Of

The conjecture discussed in this paper was that the daily number of certified cases of COVID-19 is direct correlated to the average particular matter (PM) concentrations observed several days before when the contagions occurred (short-term effect), and this correlation is higher for areas with a higher average seasonal PM concentration, as a measure of prolonged exposure to a polluted environment (long-term effect). Furthermore, the correlations between the daily COVID-19 new cases and the mobility trips and those between the daily PM concentrations and mobility trips were also investigated. Correlation analyses were performed for the application case study consisting in 13 of the main Italian cities, through the national air quality and mobility monitoring systems. Data analyses showed that the mobility restrictions performed during the lockdown produced a significant improvement in air quality with an average PM concentrations reduction of about 15%, with maximum variations ranging between 25% and 42%. Estimation results showed a positive correlation (stronger for the more highly polluted cities) between the daily COVID-19 cases and both the daily PM concentrations and mobility trips measured about three weeks before, when probably the contagion occurred. The obtained results are original, and if confirmed in other studies, it would lay the groundwork for the definition of the main context variables which influenced the COVID-19 spread. The findings highlighted in this research also supported by the evidence in the literature and allow concluding that PM concentrations and mobility habits could be considered as potential early indicators of COVID-19 circulation in outdoor environments. However, the obtained results pose significant ethical questions about the proper urban and transportation planning; the most polluted cities have not only worst welfare for their citizens but, as highlighted in this research, could lead to a likely greater spread of current and future respiratory and/or pulmonary health emergencies. The lesson to be learned by this global pandemic will help planners to better preserve the air quality of our cities in the post-COVID-19 era.

Emplacing Berlin: Digital Itineraries and Short-term Study Abroad in the City

2018 ◽  
Vol 12 (1) ◽  
pp. 26-36 ◽  
Author(s):  
Richard B. Apgar
Keyword(s):  
Study Abroad ◽  
Urban Landscape ◽  
Physical Space ◽  
Short Term ◽  
Study Abroad Programs ◽  
Term Study ◽  
Digital Maps ◽  
Short Term Study ◽  
The City

As destination of choice for many short-term study abroad programs, Berlin offers students of German language, culture and history a number of sites richly layered with significance. The complexities of these sites and the competing narratives that surround them are difficult for students to grasp in a condensed period of time. Using approaches from the spatial humanities, this article offers a case study for enhancing student learning through the creation of digital maps and itineraries in a campus-based course for subsequent use during a three-week program in Berlin. In particular, the concept of deep mapping is discussed as a means of augmenting understanding of the city and its history from a narrative across time to a narrative across the physical space of the city. As itineraries, these course-based projects were replicated on site. In moving from the digital environment to the urban landscape, this article concludes by noting meanings uncovered and narratives formed as we moved through the physical space of the city.

Indoor and outdoor air quality monitoring in hemp house — Case study

2011 ◽  
Vol 6 (3) ◽  
pp. 63-72 ◽  
Author(s):  
Jarmila Rimbalová ◽  
Silvia Vilčeková ◽  
Adriana Eštoková
Keyword(s):  
Air Quality ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Outdoor Air ◽  
Outdoor Air Quality ◽  
Indoor And Outdoor
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