scholarly journals Development of Land Use Regression Model for Seasonal Variation of Nitrogen Dioxide (NO2) in Lahore, Pakistan

2021 ◽  
Vol 13 (9) ◽  
pp. 4933
Author(s):  
Saimar Pervez ◽  
Ryuta Maruyama ◽  
Ayesha Riaz ◽  
Satoshi Nakai
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Regression Model ◽  
Urban Areas ◽  
Industrial Development ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Land Use Classification ◽  
Land Use Regression ◽  
Air Exposure

Ambient air pollution and its exposure has been a worldwide issue and can increase the possibility of health risks especially in urban areas of developing countries having the mixture of different air pollution sources. With the increase in population, industrial development and economic prosperity, air pollution is one of the biggest concerns in Pakistan after the occurrence of recent smog episodes. The purpose of this study was to develop a land use regression (LUR) model to provide a better understanding of air exposure and to depict the spatial patterns of air pollutants within the city. Land use regression model was developed for Lahore city, Pakistan using the average seasonal concentration of NO2 and considering 22 potential predictor variables including road network, land use classification and local specific variable. Adjusted explained variance of the LUR models was highest for post-monsoon (77%), followed by monsoon (71%) and was lowest for pre-monsoon (70%). This is the first study conducted in Pakistan to explore the applicability of LUR model and hence will offer the application in other cities. The results of this study would also provide help in promoting epidemiological research in future.

scholarly journals A land use regression model for explaining spatial variation in air pollution levels using a wind sector based approach

2018 ◽  
Vol 630 ◽  
pp. 1324-1334 ◽  
Author(s):  
O. Naughton ◽  
A. Donnelly ◽  
P. Nolan ◽  
F. Pilla ◽  
B.D. Misstear ◽  
...  
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Regression Model ◽  
Spatial Variation ◽  
Land Use Regression ◽  
Pollution Levels

scholarly journals P223 Influence of ambient air pollution on RA disease activity scores

Rheumatology ◽  
2020 ◽  
Vol 59 (Supplement_2) ◽  
Author(s):  
Ahmad R Alsaber ◽  
Jiazhu Pan ◽  
Adeeba Al-Herz ◽  
Dhary S Alkandary ◽  
Adeeba Al-Hurban ◽  
...  
Keyword(s):  
Air Pollution ◽  
Linear Regression ◽  
Regression Model ◽  
Disease Activity ◽  
Linear Regression Model ◽  
Activity Index ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Positive Effects ◽  
Das 28

Abstract Background This study aims to estimate the influence of air pollution ambients using the Air Quality Index (AQI) to Rheumatoid Arthritis (RA) disease activity. Disease Activity Score with 28 examined joints (DAS-28) and Clinical Disease Activity Index (CDAI) considered as disease activity indices for RA patients in the state of Kuwait. Methods Data for patients with RA disease were collected from Kuwait Registry for Rheumatic Diseases (KRRD) from 2013 to 2017. Moreover, data on air pollution obtained from The Kuwait Environmental Public Authority (K-EPA) during the same period. Statistical analysis was conducted using STATA to highlight the significant association between study variables. Descriptive statistics, correlation analysis and linear regression model techniques were employed to estimate the significant associations between RA disease activity represented by DAS-28 and CDAI; with air pollution components (PM10, NO2, SO2, O3, and CO). Multiple Imputation by Chained Equations (MICE) algorithm was also employed to tackle the value of the missing data for air pollution data. Results Total of 9,875 patients visits included in the analysis that matching with air pollution information from K-EPA database according to date and patient living address governorate. The study found SO2 and NO2 were significantly associated with RA disease activity using DAS-28 index, also, for CDAI index as well. For the score of RA disease activity using DAS-28 index, the correlation results show a positive significant correlation with exposure of SO2 using AQI (rp = 0.07), also the same results with the with the exposure of NO2 using AQI (rp = 0.07). The final model is demonstrating the effect from air-pollutants gaseous with RA factors (Swollen, RF, anti-CCP, ESR, CRP) on RA disease activity. The AQI of NO2 and SO2 still showed positive associations with disease activity performance of RA. The linear regression model shows a positive effects of NO2 (beta = 0.003, 95% CI: 0.002-0.005) and (beta = 0.048, 95\% CI: 0.030-0.066) for DAS-28 and CDAI respectively, where for SO2, the results shows positive significant effect with (beta = 0.003, 95% CI: 0.0004-0.005) and (beta = 0.044, 95% CI: 0.018-0.070) for DAS-28 and CDAI respectively. Conclusion In conclusion, our study showed that air ambients were significantly correlated to RA disease activity scores and should be considered as a possible risk factor for RA activity. Disclosures A.R. Alsaber None. J. Pan None. A. Al-Herz None. D.S. Alkandary None. A. Al-Hurban None. P. Setiya None.

scholarly journals Global Land Use Regression Model for Nitrogen Dioxide Air Pollution

2017 ◽  
Vol 51 (12) ◽  
pp. 6957-6964 ◽  
Author(s):  
Andrew Larkin ◽  
Jeffrey A. Geddes ◽  
Randall V. Martin ◽  
Qingyang Xiao ◽  
Yang Liu ◽  
...  
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Nitrogen Dioxide ◽  
Regression Model ◽  
Land Use Regression ◽  
Global Land
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