Dataset Information

PM2.5, Population Exposure and Economic Effects in Urban Agglomerations of China Using Ground-Based Monitoring Data.

ABSTRACT: This paper adopts the PM2.5 concentration data obtained from 1497 station-based monitoring sites, population and gross domestic product (GDP) census data, revealing population exposure and economic effects of PM2.5 in four typical urban agglomerations of China, i.e., Beijing-Tianjin-Hebei (BTH), the Yangtze River delta (YRD), the Pearl River delta (PRD), and Chengdu-Chongqing (CC). The Cokriging interpolation method was used to estimate the PM2.5 concentration from station-level to grid-level. Next, an evaluation was conducted mainly at the grid-level with a cell size of 1 × 1 km, assisted by the urban agglomeration scale. Criteria including the population-weighted mean, the cumulative percent distribution and the correlation coefficient were applied in our evaluation. The results showed that the spatial pattern of population exposure in BTH was consistent with that of PM2.5 concentration, as well as changes in elevation. The topography was also an important factor in the accumulation of PM2.5 in CC. Moreover, the most polluted urban agglomeration based on the population-weighted mean was BTH, while the least was PRD. In terms of the cumulative percent distribution, only 0.51% of the population who lived in the four urban agglomerations, and 2.33% of the GDP that was produced in the four urban agglomerations, were associated with an annual PM2.5 concentration smaller than the Chinese National Ambient Air Quality Standard of 35 µg/m³. This indicates that the majority of people live in the high air polluted areas, and economic development contributes to air pollution. Our results are supported by the high correlation between population exposure and the corresponding GDP in each urban agglomeration.

SUBMITTER: Shen Y

PROVIDER: S-EPMC5551154 | biostudies-other | 2017 Jul

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:Atmospheric fine particulate matter (PM2.5) causes severe haze in China and is regarded as a threat to human health. The health effects of PM2.5 vary location by location due to the variation in size distribution, chemical com position, and sources. In this study, the cytotoxicity effect, oxidative stress, and gene expression regulation of PM2.5 in Chengdu and Chongqing, two typical urban areas in southern China, were evaluated. Urban PM2.5 in summer and winter significantly inhibited cell viability and increased reactive oxygen species (ROS) levels in A549 cells. Notably, PM2.5 in winter exhibited higher cytotoxicity and ROS level than summer. Moreover, in this study, PM2.5 commonly induced cancer-related gene expression such as cell adhesion molecule 1(PECAM1), interleukin 24 (IL24), and cytochrome P450 (CYP1A1); meanwhile, PM2.5 commonly acted on cancer-related biological functions such as cell-substrate junction, cell-cell junction, and focal adhesion. In partic ular, PM2.5 in Chengdu in summer had the highest carcinogenic potential among PM2.5 at the two sites in summer and winter. Importantly, cancer-related genes were uniquely targeted by PM2.5, such as epithelial splicing regu latory protein 1 (ESRP1) and membrane-associated ring-CH-type finger 1 (1-Mar) by Chengdu summer PM2.5; collagen type IX alpha 3 chain (COL9A3) by Chengdu winter PM2.5; SH2 domain-containing 1B (SH2D1B) by Chongqing summer PM2.5; and interleukin 1 receptor-like 1 (IL1RL1) and zinc finger protein 42 (ZNF423) by Chongqing winter PM2.5. Meanwhile, important cancer-related biological functions were specially induced by PM2.5, such as cell cycle checkpoint by Chengdu summer PM2.5; macromolecule methylation by Chengdu win ter PM2.5; endoplasmic reticulum-Golgi intermediate compartment membrane by Chongqing summer PM2.5;and cellular lipid catabolic process by Chongqing winter PM2.5. Conclusively, in the typical urban areas of southern China, both summer and winter PM2.5 illustrated significant gene regulation effects. This study contrib utes to evaluating the adverse health effects of PM2.5 in southern China and providing public health suggestions for policymakers.

Project description:To evaluate the effectiveness of alternative policies and measures to reduce air pollution effects on urban citizen's health, population exposure assessments are needed. Due to road traffic emissions being a major source of emissions and exposure in European cities, it is necessary to account for differentiated transport environments in population dynamics for exposure studies. In this study, we applied a modelling system to evaluate population exposure in the urban area of Hamburg in 2016. The modeling system consists of an urban-scale chemistry transport model to account for ambient air pollutant concentrations and a dynamic time-microenvironment-activity (TMA) approach, which accounts for population dynamics in different environments as well as for infiltration of outdoor to indoor air pollution. We integrated different modes of transport in the TMA approach to improve population exposure assessments in transport environments. The newly developed approach reports 12% more total exposure to NO2 and 19% more to PM2.5 compared with exposure estimates based on residential addresses. During the time people spend in different transport environments, the in-car environment contributes with 40% and 33% to the annual sum of exposure to NO2 and PM2.5, in the walking environment with 26% and 30%, in the cycling environment with 15% and 17% and other environments (buses, subway, suburban, and regional trains) with less than 10% respectively. The relative contribution of road traffic emissions to population exposure is highest in the in-car environment (57% for NO2 and 15% for PM2.5). Results for population-weighted exposure revealed exposure to PM2.5 concentrations above the WHO AQG limit value in the cycling environment. Uncertainties for the exposure contributions arising from emissions and infiltration from outdoor to indoor pollutant concentrations range from -12% to +7% for NO2 and PM2.5. The developed "dynamic transport approach" is integrated in a computationally efficient exposure model, which is generally applicable in European urban areas. The presented methodology is promoted for use in urban mobility planning, e.g., to investigate on policy-driven changes in modal split and their combined effect on emissions, population activity and population exposure.

Dataset Information

PM2.5, Population Exposure and Economic Effects in Urban Agglomerations of China Using Ground-Based Monitoring Data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets