15 Years of Air Quality (AQ) Objective Analysis Mapping over North America Using Real-Time Observations and Canadian Operational AQ Forecast Models

2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Sylvain Ménard ◽  
Alain Robichaud ◽  
Richard Ménard ◽  
Didier Davignon
Keyword(s):  
Air Quality ◽  
North America ◽  
Real Time ◽  
Objective Analysis ◽  
Forecast Models

scholarly journals Multi-year objective analyses of warm season ground-level ozone and PM<sub>2.5</sub> over North America using real-time observations and Canadian operational air quality models

2013 ◽  
Vol 13 (5) ◽  
pp. 13967-14035 ◽  
Author(s):  
A. Robichaud ◽  
R. Ménard
Keyword(s):  
Air Quality ◽  
North America ◽  
Warm Season ◽  
Ground Level ◽  
Objective Analysis ◽  
Error Statistics ◽  
Ground Level Ozone ◽  
Air Quality Forecast ◽  
Background Check

Abstract. We present multi-year objective analyses (OA) on a high spatio-temporal resolution (15 or 21 km, every hour) for the warm season period (1 May–31 October) for ground-level ozone (2002–2012) and for fine particulate matter (diameter less than 2.5 microns (PM2.5)) (2004–2012). The OA used here combines the Canadian Air Quality forecast suite with US and Canadian surface air quality monitoring sites. The analysis is based on an optimal interpolation with capabilities for adaptive error statistics for ozone and PM2.5 and an explicit bias correction scheme for the PM2.5 analyses. The estimation of error statistics has been computed using a modified version of the Hollingsworth–Lönnberg's (H–L) method. Various quality controls (gross error check, sudden jump test and background check) have been applied to the observations to remove outliers. An additional quality control is applied to check the consistency of the error statistics estimation model at each observing station and for each hour. The error statistics are further tuned "on the fly" using a χ2 (chi-square) diagnostic, a procedure which verifies significantly better than without tuning. Successful cross-validation experiments were performed with an OA set-up using 90% of observations to build the objective analysis and with the remainder left out as an independent set of data for verification purposes. Furthermore, comparisons with other external sources of information (global models and PM2.5 satellite surface derived measurements) show reasonable agreement. The multi-year analyses obtained provide relatively high precision with an absolute yearly averaged systematic error of less than 0.6 ppbv (parts per billion by volume) and 0.7 μg m−3 (micrograms per cubic meter) for ozone and PM2.5 respectively and a random error generally less than 9 ppbv for ozone and under 12 μg m−3 for PM2.5. In this paper, we focus on two applications: (1) presenting long term averages of objective analysis and analysis increments as a form of summer climatology and (2) analyzing long term (decadal) trends and inter-annual fluctuations using OA outputs. Our results show that high percentiles of ozone and PM2.5 are both following a decreasing trend overall in North America with the eastern part of United States (US) presenting the highest decrease likely due to more effective pollution controls. Some locations, however, exhibited an increasing trend in the mean ozone and PM2.5 such as the northwestern part of North America (northwest US and Alberta). The low percentiles are generally rising for ozone which may be linked to increasing emissions from emerging countries and the resulting pollution brought by the intercontinental transport. After removing the decadal trend, we demonstrate that the inter-annual fluctuations of the high percentiles are significantly correlated with temperature fluctuations for ozone and precipitation fluctuations for PM2.5. We also show that there was a moderately significant correlation between the inter-annual fluctuations of the high percentiles of ozone and PM2.5 with economic indices such as the Industrial Dow Jones and/or the US gross domestic product growth rate.

scholarly journals A Comprehensive Real-Time Indoor Air-Quality Level Indicator

2016 ◽  
Vol 8 (9) ◽  
pp. 881 ◽  
Author(s):  
Jungho Kang ◽  
Kwang-Il Hwang
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Real Time ◽  
Indoor Air ◽  
Quality Level ◽  
Level Indicator

scholarly journals Real-time Air Quality Index monitoring experiments using SDS011 sensors and raspberry pi

2021 ◽  
Vol 1098 (4) ◽  
pp. 042090
Author(s):  
D Kurnia ◽  
F S Hadisantoso ◽  
A A Suprianto ◽  
E A Nugroho ◽  
J Janizal
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Quality Index ◽  
Air Quality Index ◽  
Raspberry Pi

scholarly journals How Can Existing Ground-Based Profiling Instruments Improve European Weather Forecasts?

2019 ◽  
Vol 100 (4) ◽  
pp. 605-619 ◽  
Author(s):  
A. J. Illingworth ◽  
D. Cimini ◽  
A. Haefele ◽  
M. Haeffelin ◽  
M. Hervo ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Positive Impact ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Time Data ◽  
Weather Forecasts ◽  
Forecast Models ◽  
Wind Lidar ◽  
Microwave Radiometers

Abstract To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.

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