Dataset Information

PM2.5 Pollutant in Asia-A Comparison of Metropolis Cities in Indonesia and Taiwan.

ABSTRACT: Air pollution has emerged as a significant health, environmental, economic, and social problem all over the world. In this study, geospatial technologies coupled with a LUR (Land Use Regression) approach were applied to assess the spatial-temporal distribution of fine particulate (PM2.5). In-situ observations of air pollutants from ground monitoring stations from 2016-2018 were used as dependent variables, while the land-use/land cover, a NDVI (Normalized Difference Vegetation Index) from a MODIS sensors, and meteorology data allocations surrounding the monitoring stations from 0.25-5 km buffer ranges were collected as spatial predictors from GIS and remote sensing databases. A linear regression method was developed for the LUR model and 10-fold cross-validation was used to assess the model robustness. The R2 model obtained was 56% for DKI Jakarta, Indonesia, and 83% for Taipei Metropolis, Taiwan. According to the results of the PM2.5 model, the essential predictors for DKI Jakarta were influenced by temperature, NDVI, humidity, and residential area, while those for the Taipei Metropolis region were influenced by PM10, NO2, SO2, UV, rainfall, spring, main road, railroad, airport, proximity to airports, mining areas, and NDVI. The validation of the results of the estimated PM2.5 distribution use 10-cross validation with indicated R2 values of 0.62 for DKI Jakarta and 0.84 for Taipei Metropolis. The results of cross-validation show the strength of the model.

SUBMITTER: Kusuma WL

PROVIDER: S-EPMC6950409 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Publications

PM<sub>2.5</sub> Pollutant in Asia-A Comparison of Metropolis Cities in Indonesia and Taiwan.

Kusuma Widya Liadira WL Chih-Da Wu W Yu-Ting Zeng Z Hapsari Handayani Hepi HH Muhamad Jaelani Lalu JL

International journal of environmental research and public health 20191205 24

Air pollution has emerged as a significant health, environmental, economic, and social problem all over the world. In this study, geospatial technologies coupled with a LUR (Land Use Regression) approach were applied to assess the spatial-temporal distribution of fine particulate (PM<sub>2.5</sub>). In-situ observations of air pollutants from ground monitoring stations from 2016-2018 were used as dependent variables, while the land-use/land cover, a NDVI (Normalized Difference Vegetation Index) ...[more]

PMID: 31817416

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Project description:Street food makes a significant contribution to the diet of many dwellers in low- and middle-income countries and its trade is a well-developed activity in the central Asian region. However, data on its purchase and nutritional value is still scarce. This study aimed to describe street food purchasing patterns in central Asia, according to time and place of purchase. A multicentre cross-sectional study was conducted in 2016/2017 in the main urban areas of four central Asian countries: Dushanbe (Tajikistan), Bishkek (Kyrgyzstan), Ashgabat (Turkmenistan) and Almaty (Kazakhstan). Street food markets (n = 34) and vending sites (n = 390) were selected by random and systematic sampling procedures. Data on the purchased foods and beverages were collected by direct observation. Time and geographic location of the purchases was registered, and their nutritional composition was estimated. A total of 714 customers, who bought 852 foods, were observed. Customers' influx, buying rate and purchase of industrial food were higher in city centers compared to the outskirts (median: 4.0 vs. 2.0 customers/10 min, p < 0.001; 5.0 vs. 2.0 food items/10 min, p < 0.001; 36.2 vs. 28.7%, p = 0.004). Tea, coffee, bread and savory pastries were most frequently purchased in the early morning, bread, main dishes and savory pastries during lunchtime, and industrial products in the mid-morning and mid-afternoon periods. Energy and macronutrient density was highest at 11:00-12:00 and lowest at 09:00-10:00. Purchases were smaller but more energy-dense in city centers, and higher in saturated and trans-fat in the peripheries. This work provides an overview of the street food buying habits in these cities, which in turn reflect local food culture. These findings from the main urban areas of four low- and middle-income countries which are currently under nutrition transition can be useful when designing public health interventions customized to the specificities of these food environments and their customers.

Dataset Information

PM2.5 Pollutant in Asia-A Comparison of Metropolis Cities in Indonesia and Taiwan.

Publications

PM<sub>2.5</sub> Pollutant in Asia-A Comparison of Metropolis Cities in Indonesia and Taiwan.

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