scholarly journals Evaluating the sensitivity of fine particulate matter (PM<sub>2.5</sub>) simulations to chemical mechanism in Delhi

2020 ◽  
Author(s):  
Chinmay Jena ◽  
Sachin D. Ghude ◽  
Rachana Kulkarni ◽  
Sreyashi Debnath ◽  
Rajesh Kumar ◽  
...  

Abstract. Elevated levels of fine particulate matter (PM2.5) during winter-time have become one of the most important environmental concerns over the Indo-Gangetic Plain (IGP) region of India, and particularly for Delhi. Accurate reconstruction of PM2.5, its optical properties, and dominant chemical components over this region is essential to evaluate the performance of the air quality models. In this study, we investigated the effect of three different aerosol mechanisms coupled with gas-phase chemical schemes on simulated PM2.5 mass concentration in Delhi using the Weather Research and Forecasting model with the Chemistry module (WRF-Chem). The model was employed to cover the entire northern region of India at 10 km horizontal spacing. Results were compared with comprehensive filed data set on dominant PM2.5 chemical compounds from the Winter Fog Experiment (WiFEX) at Delhi, and surface PM2.5 observations in Delhi (17 sites), Punjab (3 sites), Haryana (4 sites), Uttar Pradesh (7 sites) and Rajasthan (17 sites). The Model for Ozone and Related Chemical Tracers (MOZART-4) gas-phase chemical mechanism coupled with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) aerosol scheme (MOZART-GOCART) were selected in the first experiment as it is currently employed in the operational air quality forecasting system of Ministry of Earth Sciences (MoES), Government of India. Other two simulations were performed with the MOZART-4 gas-phase chemical mechanism coupled with the Model for Simulating Aerosol Interactions and Chemistry (MOZART-MOSAIC), and Carbon Bond 5 (CB-05) gas-phase mechanism couple with the Modal Aerosol Dynamics Model for Europe/Secondary Organic Aerosol Model (CB05-MADE/SORGAM) aerosol mechanisms. The evaluation demonstrated that chemical mechanisms affect the evolution of gas-phase precursors and aerosol processes, which in turn affect the optical depth and overall performance of the model for PM2.5. All the three coupled schemes, MOZART-GOCART, MOZART-MOSAIC, and CB05-MADE/SORGAM, underestimate the observed concentrations of major aerosol composition (NO3−, SO42−, Cl−, BC, OC, and NH4+) and precursor gases (HNO3, NH3, SO2, NO2, and O3) over Delhi. Comparison with observations suggests that the simulations using MOZART-4 gas-phase chemical mechanism with MOSAIC aerosol performed better in simulating aerosols over Delhi and its optical depth over the IGP. The lowest NMB (−18.8 %, MB = −27.4 μg/m3) appeared for the simulations using MOZART-MOSAIC scheme, whereas the NMB was observed 32.5 % (MB = −47.5 μg/m3) for CB05-MADE/SORGAM and −53.3 % (MB = −78 μg/m3) for MOZART-GOCART scheme.

2019 ◽  
Vol 12 (12) ◽  
pp. 6385-6399 ◽  
Author(s):  
Bonne Ford ◽  
Jeffrey R. Pierce ◽  
Eric Wendt ◽  
Marilee Long ◽  
Shantanu Jathar ◽  
...  

Abstract. A pilot field campaign was conducted in the fall and winter of 2017 in northern Colorado to test the deployment of the Aerosol Mass and Optical Depth (AMOD) instrument as part of the Citizen-Enabled Aerosol Measurements for Satellites (CEAMS) network. Citizen scientists were recruited to set up the device to take filter and optical measurements of aerosols in their backyards. The goal of the network is to provide more surface particulate matter and aerosol optical depth (AOD) measurements to increase the spatial and temporal resolution of ratios of fine particulate matter (PM2.5) to AOD and to improve satellite-based estimates of air quality. Participants collected 65 filters and 160 multi-wavelength AOD measurements, from which 109 successful PM2.5 : AOD ratios were calculated. We show that PM2.5, AOD, and their ratio (PM2.5 : AOD) often vary substantially over relatively short spatial scales; this spatial variation is not typically resolved by satellite- and model-based PM2.5 exposure estimates. The success of the pilot campaign suggests that citizen-science networks are a viable means for providing new insight into surface air quality. We also discuss lessons learned and AMOD design modifications, which will be used in future wider deployments of the CEAMS network.


2021 ◽  
Author(s):  
Shixian Zhai ◽  
Daniel J. Jacob ◽  
Jared F. Brewer ◽  
Ke Li ◽  
Jonathan M. Moch ◽  
...  

Abstract. Geostationary satellite sensors over East Asia (GOCI and AHI) are now providing continuous mapping of aerosol optical depth (AOD) at 550 nm to improve monitoring of fine particulate matter (PM2.5) air quality. Here we evaluate our understanding of the physical relationships between AOD and PM2.5 over East Asia by using the GEOS-Chem atmospheric chemistry model to simulate observations from multiple sources: 1) the joint NASA-NIER Korea – United States Air Quality aircraft campaign over South Korea (KORUS-AQ; May–June 2016); 2) AODs from the AERONET ground-based network; 3) AOD from a new GOCI/AHI fused product; and 4) surface PM2.5 networks in South Korea and China. The KORUS-AQ data show that 550 nm AOD is mainly contributed by sulfate-nitrate-ammonium (SNA) and organic aerosols in the planetary boundary layer (PBL), despite large dust concentrations in the free troposphere, reflecting the optically effective size and the high hygroscopicity of the PBL aerosols. Although GEOS-Chem is successful in reproducing the KORUS-AQ vertical profiles of aerosol mass, its ability to link AOD to PM2.5 is limited by under-accounting of coarse PM and by a large overestimate of nighttime PM2.5 nitrate. A broader analysis of the GOCI/AHI AOD data over East Asia in different seasons shows agreement with AERONET AODs and a spatial distribution consistent with surface PM2.5 network data. The AOD observations over North China show a summer maximum and winter minimum, opposite in phase to surface PM2.5. This is due to low PBL depths compounded by high residential coal emissions in winter, and high relative humidity (RH) in summer. Seasonality of AOD and PM2.5 over South Korea is much weaker, reflecting weaker variation of PBL depth and lack of residential coal emissions. Physical interpretation of the satellite AOD data in terms of surface PM2.5 is sensitive to accurate information on aerosol size distributions, PBL depths, RH, the role of coarse particles, and diurnal variation of PM2.5.


Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 302
Author(s):  
Rajesh Kumar ◽  
Piyush Bhardwaj ◽  
Gabriele Pfister ◽  
Carl Drews ◽  
Shawn Honomichl ◽  
...  

This paper describes a quasi-operational regional air quality forecasting system for the contiguous United States (CONUS) developed at the National Center for Atmospheric Research (NCAR) to support air quality decision-making, field campaign planning, early identification of model errors and biases, and support the atmospheric science community in their research. This system aims to complement the operational air quality forecasts produced by the National Oceanic and Atmospheric Administration (NOAA), not to replace them. A publicly available information dissemination system has been established that displays various air quality products, including a near-real-time evaluation of the model forecasts. Here, we report the performance of our air quality forecasting system in simulating meteorology and fine particulate matter (PM2.5) for the first year after our system started, i.e., 1 June 2019 to 31 May 2020. Our system shows excellent skill in capturing hourly to daily variations in temperature, surface pressure, relative humidity, water vapor mixing ratios, and wind direction but shows relatively larger errors in wind speed. The model also captures the seasonal cycle of surface PM2.5 very well in different regions and for different types of sites (urban, suburban, and rural) in the CONUS with a mean bias smaller than 1 µg m−3. The skill of the air quality forecasts remains fairly stable between the first and second days of the forecasts. Our air quality forecast products are publicly available at a NCAR webpage. We invite the community to use our forecasting products for their research, as input for urban scale (<4 km), air quality forecasts, or the co-development of customized products, just to name a few applications.


2014 ◽  
Vol 89 ◽  
pp. 189-198 ◽  
Author(s):  
Alexandra A. Chudnovsky ◽  
Petros Koutrakis ◽  
Itai Kloog ◽  
Steven Melly ◽  
Francesco Nordio ◽  
...  

2014 ◽  
Vol 7 (6) ◽  
pp. 2557-2579 ◽  
Author(s):  
S. Archer-Nicholls ◽  
D. Lowe ◽  
S. Utembe ◽  
J. Allan ◽  
R. A. Zaveri ◽  
...  

Abstract. We have made a number of developments to the Weather, Research and Forecasting model coupled with Chemistry (WRF-Chem), with the aim of improving model prediction of trace atmospheric gas-phase chemical and aerosol composition, and of interactions between air quality and weather. A reduced form of the Common Reactive Intermediates gas-phase chemical mechanism (CRIv2-R5) has been added, using the Kinetic Pre-Processor (KPP) interface, to enable more explicit simulation of VOC degradation. N2O5 heterogeneous chemistry has been added to the existing sectional MOSAIC aerosol module, and coupled to both the CRIv2-R5 and existing CBM-Z gas-phase schemes. Modifications have also been made to the sea-spray aerosol emission representation, allowing the inclusion of primary organic material in sea-spray aerosol. We have worked on the European domain, with a particular focus on making the model suitable for the study of nighttime chemistry and oxidation by the nitrate radical in the UK atmosphere. Driven by appropriate emissions, wind fields and chemical boundary conditions, implementation of the different developments are illustrated, using a modified version of WRF-Chem 3.4.1, in order to demonstrate the impact that these changes have in the Northwest European domain. These developments are publicly available in WRF-Chem from version 3.5.1 onwards.


2017 ◽  
Author(s):  
Giovanni Di Virgilio ◽  
Melissa Anne Hart ◽  
Ningbo Jiang

Abstract. Internationally, severe wildfires are an escalating problem likely to worsen given projected changes to climate. Hazard reduction burns (HRB) are used to suppress wildfire occurrences, but they generate considerable emissions of atmospheric fine particulate matter, which depending upon prevailing atmospheric conditions, can degrade air quality. Our objectives are to improve understanding of the relationships between meteorological conditions and air quality during HRBs in Sydney, Australia. We identify the primary meteorological covariates linked to high PM2.5 pollution (particulates


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