Estimating daily and intra-daily PM10 and PM2.5 in Israel using a spatio-temporal hybrid modeling approach

Shtein, Alexandra; Karnieli, Arnon; Katra, Itzhak; Raz, Raul; Levy, Ilan; Lyapustin, Alexei; Dorman, Michael; Broday, David M.; Kloog, Itai

doi:10.1016/j.atmosenv.2018.08.002

Cited by 39 publications

(30 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For days when AOD data are not available (because of meteorological conditions or retrieval errors) for some grid cells, the model fit a generalized additive model with a thin plate spline term of latitude and longitude to interpolate PM 2.5 . Model performance is excellent with out-of-sample cross validation R 2 values of 0.92 and 0.87 for PM less than 10 μm in diameter (PM 10 ) and PM 2.5 , respectively [31,32].…”

Section: Exposure Assessmentmentioning

confidence: 99%

“…Exposure to PM 2.5 was assessed based on a hybrid model developed by Kloog et al [30,31] utilizing daily satellite remote sensing data at 1km 2 spatial resolution. The model uses an algorithm developed by the National Aeronautics and Space Administration (NASA)called MAIAC (Multi-Angle Implementation to Atmospheric Correction) which is part of the MODIS (Moderate Resolution Imaging Spectroradiometer) system, providing satellite aerosol optical depth (AOD) data.…”

Section: Exposure Assessmentmentioning

confidence: 99%

See 1 more Smart Citation

The effect of exposure to particulate matter during pregnancy on lower respiratory tract infection hospitalizations during first year of life

et al. 2020

Self Cite

View full text Add to dashboard Cite

Background: Lower respiratory tract infections (LRTI) in early life, including pneumonia, bronchitis and bronchiolitis, can lead to decreased lung function, persistent lung damage and increased susceptibility to various respiratory diseases such as asthma. In-utero exposure to particulate matter (PM) during pregnancy may disrupt biological mechanisms that regulate fetal growth, maturation and development. We aimed to estimate the association between intrauterine exposure to PM of size < 2.5 μm in diameter (PM 2.5) and incidence of LRTIs during the first year of life. Methods: A retrospective population-based cohort study in a population of mothers and infants born in Soroka University Medical Center (SUMC) in the years 2004-2012. All infants < 1 year old that were hospitalized due to LRTIs were included. The main exposure assessment was based on a hybrid model incorporating daily satellite-based predictions at 1 km 2 spatial resolution. Data from monitoring stations was used for imputation of main exposure and other pollutants. Levels of environmental exposures were assigned to subjects based on their residential addresses and averaged for each trimester. Analysis was conducted by a multivariable generalized estimating equation (GEE) Poisson regression. Data was analyzed separately for the two main ethnic groups in the region, Jewish and Arab-Bedouin. Results: The study cohort included 57,331 deliveries that met the inclusion criteria. Overall, 1871 hospitalizations of infants < 1 year old due to pneumonia or bronchiolitis were documented. In a multivariable analysis, intrauterine exposure to high levels of PM 2.5 (> 24 μg/m 3) in the first and second trimesters was found to be adversely associated with LRTIs in the Arab-Bedouin population (1st trimester, RR = 1.31, CI 95% 1.08-1.60; 2nd trimester: RR = 1.34, CI 95% 1.09-1.66). Conclusion: Intrauterine exposure to high levels of PM 2.5 is associated with a higher risk of hospitalizations due to lower respiratory tract infections in Arab-Bedouin infants.

show abstract

Section: Exposure Assessmentmentioning

confidence: 99%

Section: Exposure Assessmentmentioning

confidence: 99%

The effect of exposure to particulate matter during pregnancy on lower respiratory tract infection hospitalizations during first year of life

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…Satellite PM estimations were based on a novel satellite spatiotemporal models developed by our group [ 44 ] for predicting PM10 and PM2.5. These relied on the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on top of the Terra and Aqua satellites, based on their overpass times which differ in time (3 h apart).…”

Section: Methodsmentioning

confidence: 99%

Validating and Comparing Highly Resolved Commercial “Off the Shelf” PM Monitoring Sensors with Satellite Based Hybrid Models, for Improved Environmental Exposure Assessment

Lesser

Katra

Dorman

et al. 2020

Sensors

Self Cite

View full text Add to dashboard Cite

Particulate matter is a common health hazard, and under certain conditions, an ecological threat. While many studies were conducted in regard to air pollution and potential effects, this paper serves as a pilot scale investigation into the spatial and temporal variability of particulate matter (PM) pollution in arid urban environments in general, and Beer-Sheva, Israel as a case study. We explore the use of commercially off the shelf (COTS) sensors, which provide an economical solution for spatio-temporal measurements. We started with a comparison process against an A-grade meteorological station, where it was shown that under specific climatic conditions, a number of COTS sensors were able to produce robust agreement (mean R2=0.93, average SD=17.5). The second stage examined the COTS sensors that were proven accurate in a mobile measurement campaign. Finally, data collected was compared to a validated satellite prediction model. We present how these tests and COTS sensor-kits could then be used to further explain the continuity and dispersion of particulate matter in similar areas.

show abstract

“…Using spatially and temporally resolved satellite-based products as a predictor allows extending the air pollution estimates to locations and time points where ground level measurements are absent. This modelling approach was used in different regions, including Europe [52,53], United States (US) [54][55][56][57], China [58], Mexico city [59], and Israel [60,61] to estimate daily PM 10 and PM 2.5 concentrations in spatial resolution of 1 × 1 km 2 and showed good performance with cross validated (cv) total R 2 ranging between 0.70-0.92, depending on the area and the specific methodology that was applied. Similar approach was used to estimate daily NO 2 concentrations in the US [62], Hong Kong [63], and Switzerland [64] with cv R 2 of 0.79, 0.84, and 0.58, respectively.…”

Section: Remote Sensingmentioning

confidence: 99%

Novel Approaches to Air Pollution Exposure and Clinical Outcomes Assessment in Environmental Health Studies

et al. 2020

Self Cite

View full text Add to dashboard Cite

An accurate assessment of pollutants’ exposure and precise evaluation of the clinical outcomes pose two major challenges to the contemporary environmental health research. The common methods for exposure assessment are based on residential addresses and are prone to many biases. Pollution levels are defined based on monitoring stations that are sparsely distributed and frequently distanced far from residential addresses. In addition, the degree of an association between outdoor and indoor air pollution levels is not fully elucidated, making the exposure assessment all the more inaccurate. Clinical outcomes’ assessment, on the other hand, mostly relies on the access to medical records from hospital admissions and outpatients’ visits in clinics. This method differentiates by health care seeking behavior and is therefore, problematic in evaluation of an onset, duration, and severity of an outcome. In the current paper, we review a number of novel solutions aimed to mitigate the aforementioned biases. First, a hybrid satellite-based modeling approach provides daily continuous spatiotemporal estimations with improved spatial resolution of 1 × 1 km2 and 200 × 200 m2 grid, and thus allows a more accurate exposure assessment. Utilizing low-cost air pollution sensors allowing a direct measurement of indoor air pollution levels can further validate these models. Furthermore, the real temporal-spatial activity can be assessed by GPS tracking devices within the individuals’ smartphones. A widespread use of smart devices can help with obtaining objective measurements of some of the clinical outcomes such as vital signs and glucose levels. Finally, human biomonitoring can be efficiently done at a population level, providing accurate estimates of in-vivo absorbed pollutants and allowing for the evaluation of body responses, by biomarkers examination. We suggest that the adoption of these novel methods will change the research paradigm heavily relying on ecological methodology and support development of the new clinical practices preventing adverse environmental effects on human health.

show abstract

Estimating daily and intra-daily PM10 and PM2.5 in Israel using a spatio-temporal hybrid modeling approach

Cited by 39 publications

References 41 publications

The effect of exposure to particulate matter during pregnancy on lower respiratory tract infection hospitalizations during first year of life

The effect of exposure to particulate matter during pregnancy on lower respiratory tract infection hospitalizations during first year of life

Validating and Comparing Highly Resolved Commercial “Off the Shelf” PM Monitoring Sensors with Satellite Based Hybrid Models, for Improved Environmental Exposure Assessment

Novel Approaches to Air Pollution Exposure and Clinical Outcomes Assessment in Environmental Health Studies

Contact Info

Product

Resources

About