Toward the next generation of air quality monitoring: Particulate Matter

2013 ◽  
Vol 80 ◽  
pp. 584-590 ◽  
Author(s):  
Jill Engel-Cox ◽  
Nguyen Thi Kim Oanh ◽  
Aaron van Donkelaar ◽  
Randall V. Martin ◽  
Erica Zell
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Next Generation

scholarly journals One-Year Simulation of Ozone and Particulate Matter in China Using WRF/CMAQ Modeling System

2016 ◽  
Author(s):  
Jianlin Hu ◽  
Jianjun Chen ◽  
Qi Ying ◽  
Hongliang Zhang
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Model Performance ◽  
Monitoring Network ◽  
Organic Aerosol ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Low Concentration ◽  
Temporal And Spatial

Abstract. China has been experiencing severe air pollution in recent decades. Although ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research & Forecasting model (WRF) and the Community Multi-scale Air Quality model (CMAQ) was conducted to provide detailed temporal and spatial information of ozone (O3), PM2.5 total and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, over-prediction of O3 generally occurs at low concentration range while under-prediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in Southern China than in Northern, Central and Sichuan basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42−), nitrate (NO3−), ammonium (NH4+), and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of CMAQ model in reproducing severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects.

scholarly journals A Review of Low-Cost Particulate Matter Sensors from the Developers’ Perspectives

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6819
Author(s):  
Brigida Alfano ◽  
Luigi Barretta ◽  
Antonio Del Giudice ◽  
Saverio De Vito ◽  
Girolamo Di Francia ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Health Effects ◽  
Low Cost ◽  
Reference Method ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Extensive Review ◽  
Research Groups ◽  
International Regulations

The concerns related to particulate matter’s health effects alongside the increasing demands from citizens for more participatory, timely, and diffused air quality monitoring actions have resulted in increasing scientific and industrial interest in low-cost particulate matter sensors (LCPMS). In the present paper, we discuss 50 LCPMS models, a number that is particularly meaningful when compared to the much smaller number of models described in other recent reviews on the same topic. After illustrating the basic definitions related to particulate matter (PM) and its measurements according to international regulations, the device’s operating principle is presented, focusing on a discussion of the several characterization methodologies proposed by various research groups, both in the lab and in the field, along with their possible limitations. We present an extensive review of the LCPMS currently available on the market, their electronic characteristics, and their applications in published literature and from specific tests. Most of the reviewed LCPMS can accurately monitor PM changes in the environment and exhibit good performances with accuracy that, in some conditions, can reach R2 values up to 0.99. However, such results strongly depend on whether the device is calibrated or not (using a reference method) in the operative environment; if not, R2 values lower than 0.5 are observed.

scholarly journals Analysis of concentration levels of particulate matter (PM10, total suspended particulates and black smoke) in the city of Zrenjanin

2010 ◽  
Vol 64 (5) ◽  
pp. 453-458 ◽  
Author(s):  
Bogdana Vujic ◽  
Dusan Milovanovic ◽  
Dejan Ubavin
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Geographical Location ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Suspended Particulates ◽  
Black Smoke ◽  
Total Suspended Particulates ◽  
The City ◽  
Concentration Levels

Air quality monitoring on the territory of AP Vojvodina was initiated in mid 90s. During the last decade of the 20th century the development of the air quality monitoring in Serbia didn?t keep up with the pace of the other countries in the region due to political isolation and severe economic crisis. Monitoring of the particular pollutants was conducted unsystematically and sporadically. Data presented in this paper were obtained on the territory of the city of Zrenjanin, which represents typical agglomeration in the region in regard to its geographical location, population, level of industry development and the presence of natural gas as energy product in the remote and domestic heating system of residential objects. Available data on the concentration levels of PM10 (particulate matter with aerodynamic diameter less than 10 ?m), TSP (total suspended particulates) and BS (black smoke) during the period of 2005-2007 (three cold and three warm seasons) have been used in this work in order to carry out analysis and comparison of the daily concentration levels of PM10, TSP and BS and their seasonal variation.

scholarly journals One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system

2016 ◽  
Vol 16 (16) ◽  
pp. 10333-10350 ◽  
Author(s):  
Jianlin Hu ◽  
Jianjun Chen ◽  
Qi Ying ◽  
Hongliang Zhang
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Model Performance ◽  
Monitoring Network ◽  
Organic Aerosol ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Low Concentration ◽  
Temporal And Spatial

Abstract. China has been experiencing severe air pollution in recent decades. Although an ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research and Forecasting (WRF) model and the Community Multi-scale Air Quality (CMAQ) model was conducted to provide detailed temporal and spatial information of ozone (O3), total PM2.5, and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, overprediction of O3 generally occurs at low concentration range while underprediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in southern China than in northern China, central China, and Sichuan Basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42−), nitrate (NO3−), ammonium (NH4+), and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of the CMAQ model to reproduce severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects.

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