125 Satellite_NO2_LUR
| Project metadata | |
|---|---|
| Project Title | Satellite_NO2_LUR |
| Owners | Luke Knibbs |
| Project Abstract |
This project comprises work on the methods and data analysis for a satellite enhanced Land Use Regression model of NO2 pollution. Original Methodology reported in Knibbs, L. D., Hewson, M. G., Bechle, M. J., Marshall, J. D., & Barnett, A. G. (2014). A national satellite-based land-use regression model for air pollution exposure assessment in Australia. Environmental Research, 135, 204–211. doi:10.1016/j.envres.2014.09.011. |
125.1 SatNO2_1990_2005
| Accessibility | Provision Status | Licence |
|---|---|---|
| CARDAT | Identified | other |
| Metadata fields | |
|---|---|
| Short Name | SatNO2_1990_2005 |
| Title | SatNO2_1990_2005 |
| Creators | Luke Knibbs, Ivan Hanigan |
| Contact Email | car.data@sydney.edu.au |
| Abstract | The SatNO2_2006_2011 data can be adjusted using the coefficient on time from the paper. See Knibbs et al. 2018 Long-term nitrogen dioxide exposure assessment using back-extrapolation of satellite-based land-use regression models for Australia. Environmental Research 163 (2018) 16-25 |
| Study Extent | |
| Associated Parties | |
| Repository Path | projects/Satellite_NO2_LUR/SatNO2_1990_2005 |
| Repository Link | |
| External Link | |
| Recommended Citation | Knibbs, L. and Hanigan, I. (2023): SatNO2_1990_2005. CAR. (Dataset). |
125.2 SatNO2_2006_2011
| Accessibility | Provision Status | Licence |
|---|---|---|
| Restricted | Published | other |
| Metadata fields | |
|---|---|
| Short Name | SatNO2_2006_2011 |
| Title | SatNO2_2006_2011 |
| Creators | Luke Knibbs |
| Contact Email | car.data@sydney.edu.au |
| Abstract | This is the predicted annual mean values of NO2 (ppb) on Mesh Blocks (2011) from Knibbs (see paper Knibbs et al 2015). This is the SatLUR data predicted on MB 2011. NSW data provided to M Rolfe and G Morgan on 13/5/2015, rest of data provided to Ivan Hanigan on 1/4/2019. Note from Luke: Please note that there are 2 predictions for each year - one with ‘SURF’ and one with ‘COL’ - these refer to the model used to generate them. The two models give very similar results but COL has slightly better predictive ability. This might be the best place to start but we could also think about comparing them. There’s a handful of missing values - these are MBs where the necessary covariates were not available. Also see from the paper 2.2.4. ComparisonofdifferentsatelliteNO2 estimates We assessed whether surface NO2 estimates derived using surface-to-column ratios from WRF-Chem lead to models with better predictive ability for ground level NO2 than the easier to obtain estimates of tropospheric NO2 column density. For both our annual and monthly models, we examined two alternatives; one with surface NO2 estimates as a candidate variable and one with NO2 column density estimates. All other candidate variables were the same across the two models. |
| Study Extent | Meshblocks for NSW from the 2011 census boundaries. |
| Associated Parties | Ivan Hanigan |
| Repository Path | |
| Repository Link | https://cloud.car-dat.org/index.php/apps/files/?dir=/ResearchProjects_CAR/Satellite_NO2_LUR/SatNO2_2006_2011 |
| External Link | |
| Recommended Citation | Knibbs, L. (2015): Modelled yearly NO2 Satellite Land Use Regression Data by ABS Meshblock 2011 for Australia 2006-2011. CAR. (Dataset). https://cloud.car-dat.org/index.php/apps/files/?dir=/ResearchProjects_CAR/Satellite_NO2_LUR/SatNO2_2006_2011 |
125.3 SatNO2_2006_2011_Perth
| Accessibility | Provision Status | Licence |
|---|---|---|
| Restricted | Published | other |
| Metadata fields | |
|---|---|
| Short Name | SatNO2_2006_2011_Perth |
| Title | SatNO2_2006_2011_Perth |
| Creators | Luke Knibbs |
| Contact Email | car.data@sydney.edu.au |
| Abstract | This is the predicted annual mean values of NO2 (ppb) on Mesh Blocks (2011) in Perth from Knibbs (see paper Knibbs et al 2015). This is the SatLUR data predicted on MB 2011. Note from Luke: Please note that there are 2 predictions for each year - one with ‘SURF’ and one with ‘COL’ - these refer to the model used to generate them. The two models give very similar results but COL has slightly better predictive ability. This might be the best place to start but we could also think about comparing them. There’s a handful of missing values - these are MBs where the necessary covariates were not available. # also see from the paper 2.2.4. ComparisonofdifferentsatelliteNO2 estimates We assessed whether surface NO2 estimates derived using surface-to-column ratios from WRF-Chem lead to models with better predictive ability for ground level NO2 than the easier to obtain estimates of tropospheric NO2 column density. For both our annual and monthly models, we examined two alternatives; one with surface NO2 estimates as a candidate variable and one with NO2 column density estimates. All other candidate variables were the same across the two models. |
| Study Extent | |
| Associated Parties | Ivan Hanigan |
| Repository Path | |
| Repository Link | https://cloud.car-dat.org/index.php/apps/files/?dir=/ResearchProjects_CAR/Satellite_NO2_LUR/SatNO2_2006_2011_Perth |
| External Link | |
| Recommended Citation | Knibbs, L. (2016): SatNO2_2006_2011_Perth. CAR. (Dataset). https://cloud.car-dat.org/index.php/apps/files/?dir=/ResearchProjects_CAR/Satellite_NO2_LUR/SatNO2_2006_2011_Perth |
125.4 SatNO2_2012_2015
| Accessibility | Provision Status | Licence |
|---|---|---|
| Restricted | Published | other |
| Metadata fields | |
|---|---|
| Short Name | SatNO2_2012_2015 |
| Title | SatNO2_2012_2015 |
| Creators | Luke Knibbs |
| Contact Email | car.data@sydney.edu.au |
| Abstract | Modelled yearly NO2 satellite LUR data for all of Australia my ABS MeshBlock 2011. The SatNO2_2012_2015 data can be adjusted using the coefficient on time from the paper. See Knibbs et al. 2018 Long-term nitrogen dioxide exposure assessment using back-extrapolation of satellite-based land-use regression models for Australia. Environmental Research 163 (2018) 16-25. |
| Study Extent | |
| Associated Parties | |
| Repository Path | |
| Repository Link | https://cloud.car-dat.org/index.php/apps/files/?dir=/ResearchProjects_CAR/Satellite_NO2_LUR/SatNO2_2012_2015 |
| External Link | |
| Recommended Citation | Knibbs, L. (2021): Modelled yearly NO2 Satellite Land Use Regression Data by ABS Meshblock 2011 for Australia 2012-2015. CAR. (Dataset). https://cloud.car-dat.org/index.php/apps/files/?dir=/ResearchProjects_CAR/Satellite_NO2_LUR/SatNO2_2012_2015 |
125.5 SatNO2_45andUp
| Accessibility | Provision Status | Licence |
|---|---|---|
| Restricted | Identified | other |
| Metadata fields | |
|---|---|
| Short Name | SatNO2_45andUp |
| Title | SatNO2_45andUp |
| Creators | Luke Knibbs, Ivan Hanigan |
| Contact Email | car.data@sydney.edu.au |
| Abstract | This dataset is specifically designed to facilitate the application of the prediction equation derived from the Satellite Land Use Regression (SatLUR) model in predicting nitrogen dioxide (NO2) levels at specific street addresses. The dataset includes relevant variables and parameters necessary for the utilization of the prediction equation. |
| Study Extent | |
| Associated Parties | |
| Repository Path | |
| Repository Link | https://cloud.car-dat.org/index.php/apps/files/?dir=/ResearchProjects_CAR/Satellite_NO2_LUR/SatNO2_45andUp |
| External Link | |
| Recommended Citation | Knibbs, L. (2017): SatNO2_45andUp. CAR. (Dataset). https://cloud.car-dat.org/index.php/apps/files/?dir=/ResearchProjects_CAR/Satellite_NO2_LUR/SatNO2_45andUp |