338 related articles for article (PubMed ID: 29730578)
1. Spatiotemporal modeling of PM
Chen L; Gao S; Zhang H; Sun Y; Ma Z; Vedal S; Mao J; Bai Z
Environ Int; 2018 Jul; 116():300-307. PubMed ID: 29730578
[TBL] [Abstract][Full Text] [Related]
2. Spatiotemporal modeling of ozone levels in Quebec (Canada): a comparison of kriging, land-use regression (LUR), and combined Bayesian maximum entropy-LUR approaches.
Adam-Poupart A; Brand A; Fournier M; Jerrett M; Smargiassi A
Environ Health Perspect; 2014 Sep; 122(9):970-6. PubMed ID: 24879650
[TBL] [Abstract][Full Text] [Related]
3. Comparison of model estimates from an intra-city land use regression model with a national satellite-LUR and a regional Bayesian Maximum Entropy model, in estimating NO
Cowie CT; Garden F; Jegasothy E; Knibbs LD; Hanigan I; Morley D; Hansell A; Hoek G; Marks GB
Environ Res; 2019 Jul; 174():24-34. PubMed ID: 31026625
[TBL] [Abstract][Full Text] [Related]
4. Assessment and statistical modeling of the relationship between remotely sensed aerosol optical depth and PM2.5 in the eastern United States.
Paciorek CJ; Liu Y;
Res Rep Health Eff Inst; 2012 May; (167):5-83; discussion 85-91. PubMed ID: 22838153
[TBL] [Abstract][Full Text] [Related]
5. A hybrid approach to estimating national scale spatiotemporal variability of PM2.5 in the contiguous United States.
Beckerman BS; Jerrett M; Serre M; Martin RV; Lee SJ; van Donkelaar A; Ross Z; Su J; Burnett RT
Environ Sci Technol; 2013 Jul; 47(13):7233-41. PubMed ID: 23701364
[TBL] [Abstract][Full Text] [Related]
6. Evaluating heterogeneity in indoor and outdoor air pollution using land-use regression and constrained factor analysis.
Levy JI; Clougherty JE; Baxter LK; Houseman EA; Paciorek CJ;
Res Rep Health Eff Inst; 2010 Dec; (152):5-80; discussion 81-91. PubMed ID: 21409949
[TBL] [Abstract][Full Text] [Related]
7. A land use regression model using machine learning and locally developed low cost particulate matter sensors in Uganda.
Coker ES; Amegah AK; Mwebaze E; Ssematimba J; Bainomugisha E
Environ Res; 2021 Aug; 199():111352. PubMed ID: 34043968
[TBL] [Abstract][Full Text] [Related]
8. Combining Land-Use Regression and Chemical Transport Modeling in a Spatiotemporal Geostatistical Model for Ozone and PM2.5.
Wang M; Sampson PD; Hu J; Kleeman M; Keller JP; Olives C; Szpiro AA; Vedal S; Kaufman JD
Environ Sci Technol; 2016 May; 50(10):5111-8. PubMed ID: 27074524
[TBL] [Abstract][Full Text] [Related]
9. A land use regression model of nitrogen dioxide and fine particulate matter in a complex urban core in Lanzhou, China.
Jin L; Berman JD; Warren JL; Levy JI; Thurston G; Zhang Y; Xu X; Wang S; Zhang Y; Bell ML
Environ Res; 2019 Oct; 177():108597. PubMed ID: 31401375
[TBL] [Abstract][Full Text] [Related]
10. A hybrid approach to estimating long-term and short-term exposure levels of ozone at the national scale in China using land use regression and Bayesian maximum entropy.
Chen L; Liang S; Li X; Mao J; Gao S; Zhang H; Sun Y; Vedal S; Bai Z; Ma Z; Haiyu ; Azzi M
Sci Total Environ; 2021 Jan; 752():141780. PubMed ID: 32882471
[TBL] [Abstract][Full Text] [Related]
11. Space-time PM
He J; Christakos G
Environ Pollut; 2018 Sep; 240():319-329. PubMed ID: 29751328
[TBL] [Abstract][Full Text] [Related]
12. Spatial PM
de Hoogh K; Chen J; Gulliver J; Hoffmann B; Hertel O; Ketzel M; Bauwelinck M; van Donkelaar A; Hvidtfeldt UA; Katsouyanni K; Klompmaker J; Martin RV; Samoli E; Schwartz PE; Stafoggia M; Bellander T; Strak M; Wolf K; Vienneau D; Brunekreef B; Hoek G
Environ Int; 2018 Nov; 120():81-92. PubMed ID: 30075373
[TBL] [Abstract][Full Text] [Related]
13. Using MAIAC AOD to verify the PM
Li R; Ma T; Xu Q; Song X
Environ Pollut; 2018 Dec; 243(Pt A):501-509. PubMed ID: 30216882
[TBL] [Abstract][Full Text] [Related]
14. Spatiotemporal Characterization of Ambient PM2.5 Concentrations in Shandong Province (China).
Yang Y; Christakos G
Environ Sci Technol; 2015 Nov; 49(22):13431-8. PubMed ID: 26501430
[TBL] [Abstract][Full Text] [Related]
15. Spatiotemporal estimation of the PM
Zhang P; Yang L; Ma W; Wang N; Wen F; Liu Q
Environ Res; 2022 May; 208():112759. PubMed ID: 35077716
[TBL] [Abstract][Full Text] [Related]
16. Development and Evaluation of Spatio-Temporal Air Pollution Exposure Models and Their Combinations in the Greater London Area, UK.
Dimakopoulou K; Samoli E; Analitis A; Schwartz J; Beevers S; Kitwiroon N; Beddows A; Barratt B; Rodopoulou S; Zafeiratou S; Gulliver J; Katsouyanni K
Int J Environ Res Public Health; 2022 Apr; 19(9):. PubMed ID: 35564796
[TBL] [Abstract][Full Text] [Related]
17. An LUR/BME framework to estimate PM2.5 explained by on road mobile and stationary sources.
Reyes JM; Serre ML
Environ Sci Technol; 2014; 48(3):1736-44. PubMed ID: 24387222
[TBL] [Abstract][Full Text] [Related]
18. A machine learning method to estimate PM
Chen G; Li S; Knibbs LD; Hamm NAS; Cao W; Li T; Guo J; Ren H; Abramson MJ; Guo Y
Sci Total Environ; 2018 Sep; 636():52-60. PubMed ID: 29702402
[TBL] [Abstract][Full Text] [Related]
19. Application of an advanced spatiotemporal model for PM
Zhang T; Liu P; Sun X; Zhang C; Wang M; Xu J; Pu S; Huang L
Chemosphere; 2020 May; 246():125563. PubMed ID: 31884232
[TBL] [Abstract][Full Text] [Related]
20. Land use regression modelling of air pollution in high density high rise cities: A case study in Hong Kong.
Lee M; Brauer M; Wong P; Tang R; Tsui TH; Choi C; Cheng W; Lai PC; Tian L; Thach TQ; Allen R; Barratt B
Sci Total Environ; 2017 Aug; 592():306-315. PubMed ID: 28319717
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]