Evaluation of WRF-CHIMERE coupled models for the simulation of PM<sub>2.5</sub> in large East African urban conurbations

Abstract. Urban conurbations of East Africa are affected by harmful levels of air pollution. The paucity of local air quality networks and the absence of capacity to forecast air quality make it difficult to quantify the real level of air pollution in this area. The chemistry-transport model CHIMERE has been coupled with the meteorological model WRF and used to simulate hourly concentrations of Particulate Matter PM2.5 for three East African urban conurbations: Addis Ababa in Ethiopia, Nairobi in Kenya and Kampala in Uganda. Two existing emission inventories were combined to test the performance of CHIMERE as an air quality tool for a target monthly period of 2017 and the results compared against observed data from urban and rural sites. The results show that the model is able to reproduce hourly and daily temporal variability of aerosol concentrations close to observations both in urban and rural environments. CHIMERE’s performance as a tool for managing air quality was also assessed. The analysis demonstrated that despite the absence of high-resolution data and up-to-date biogenic and anthropogenic emissions, the model was able to reproduce 66–99 % of the daily PM2.5 exceedances above the WHO 24-hour mean PM2.5 guideline (25 µg m−3) in the three cities. An analysis of the 24-hour mean levels of PM2.5 was also carried out for 17 constituencies in the vicinity of Nairobi. This showed that 47 % of the constituencies in the area exhibited a low air quality index for PM2.5 in the unhealthy category for human health exposing between 10000 to 30000 people/km2 to harmful levels of air contamination.

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Pre-monsoon air quality over Lumbini, a world heritage site along the Himalayan foothills

10.5194/acp-2016-430 ◽

2016 ◽

Cited By ~ 2

Author(s):

Dipesh Rupakheti ◽

Bhupesh Adhikary ◽

Puppala S. Praveen ◽

Maheswar Rupakheti ◽

Shichang Kang ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Forest Fires ◽

Air Pollutants ◽

Transport Model ◽

World Heritage ◽

World Heritage Site ◽

Pollution Level ◽

Pollution Transport ◽

Heritage Site

Abstract. Lumbini, in southern Nepal, is a UNESCO world heritage site of universal value as the birthplace of Buddha. Poor air quality in Lumbini and surrounding regions is a great concern for public health as well as for preservation, protection and promotion of Buddhist heritage and culture. We present here results from measurements of ambient concentrations of key air pollutants (PM, BC, CO, O3) in Lumbini, first of its kind for Lumbini, conducted during an intensive measurement period of three months (April–June 2013) in the pre-monsoon season. The measurements were carried out as a part of the international air pollution measurement campaign; SusKat-ABC (Sustainable Atmosphere for the Kathmandu Valley – Atmospheric Brown Clouds). The ranges of hourly average concentrations were: PM10: 10.5–604.0 µg m−3, PM2.5: 6.1–272.2 µg m−3; BC: 0.3–30.0 µg m−3; CO: 125.0–1430.0 ppbv; and O3: 1.0–118.1 ppbv. These levels are comparable to other very heavily polluted sites throughout South Asia. The 24-h average PM2.5 and PM10 concentrations exceeded the WHO guideline very frequently (94 % and 85 % of the sampled period, respectively), which implies significant health risks for the residents and visitors in the region. These air pollutants exhibited clear diurnal cycles with high values in the morning and evening. During the study period, the worst air pollution episodes were mainly due to agro-residue burning and regional forest fires combined with meteorological conditions conducive of pollution transport to Lumbini. Fossil fuel combustion also contributed significantly, accounting for more than half of the ambient BC concentration according to aerosol spectral light absorption coefficients obtained in Lumbini. WRF-STEM, a regional chemical transport model, was used to simulate the meteorology and the concentrations of pollutants. The model was able to reproduce the variation in the pollutant concentrations well; however, estimated values were 1.5 to 5 times lower than the observed concentrations for CO and PM10 respectively. Regionally tagged CO tracers showed the majority of CO came from the upwind region of Ganges valley. The model was also used to examine the chemical composition of the aerosol mixture, indicating that organic carbon was the main constituent of fine mode PM2.5, followed by mineral dust. Given the high pollution level, there is a clear and urgent need for setting up a network of long-term air quality monitoring stations in the greater Lumbini region.

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Skill-Testing Chemical Transport Models across Contrasting Atmospheric Mixing States Using Radon-222

10.20944/preprints201811.0607.v1 ◽

2018 ◽

Author(s):

Scott D. Chambers ◽

Elise-Andree Guérette ◽

Khalia Monk ◽

Alan D. Griffiths ◽

Yang Zhang ◽

...

Keyword(s):

Air Quality ◽

Diurnal Cycle ◽

Transport Model ◽

Chemical Transport ◽

Chemical Transport Model ◽

Transport Models ◽

Potential Health ◽

Meteorological Model ◽

Model Skill ◽

Chemical Transport Models

We propose a new technique to prepare statistically-robust benchmarking data for evaluating chemical transport model meteorology and air quality parameters within the urban boundary layer. The approach employs atmospheric class-typing, using nocturnal radon measurements to assign atmospheric mixing classes, and can be applied temporally (across the diurnal cycle), or spatially (to create angular distributions of pollutants as a top-down constraint on emissions inventories). In this study only a short (<1-month) campaign is used, but grouping of the relative mixing classes based on nocturnal mean radon concentrations can be adjusted according to dataset length (i.e., number of days per category), or desired range of within-class variability. Calculating hourly distributions of observed and simulated values across diurnal composites of each class-type helps to: (i) bridge the gap between scales of simulation and observation, (ii) represent the variability associated with spatial and temporal heterogeneity of sources and meteorology without being confused by it, and (iii) provide an objective way to group results over whole diurnal cycles that separates ‘natural complicating factors’ (synoptic non-stationarity, rainfall, mesoscale motions, extreme stability, etc.) from problems related to parameterizations, or between-model differences. We demonstrate the utility of this technique using output from a suite of seven contemporary regional forecast and chemical transport models. Meteorological model skill varied across the diurnal cycle for all models, with an additional dependence on the atmospheric mixing class that varied between models. From an air quality perspective, model skill regarding the duration and magnitude of morning and evening “rush hour” pollution events varied strongly as a function of mixing class. Model skill was typically the lowest when public exposure would have been the highest, which has important implications for assessing potential health risks in new and rapidly evolving urban regions, and also for prioritizing the areas of model improvement for future applications.

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Impacts of emission changes in China from 2010 to 2017 on domestic and intercontinental air quality and health effect

10.5194/acp-2021-385 ◽

2021 ◽

Author(s):

Yuqiang Zhang ◽

Drew Shindell ◽

Karl Seltzer ◽

Lu Shen ◽

Jean-Francois Lamarque ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Air Pollutants ◽

Transport Model ◽

Surface Ozone ◽

Health Effect ◽

Premature Deaths ◽

Concentration Changes ◽

Emission Changes ◽

Related Mortality

Abstract. China has seen dramatic emission changes from 2010, especially after the implementation of Clean Air Action in 2013, with significant air quality and human health benefits observed. Air pollutants, such as PM2.5 and surface ozone, as well as their precursors, have long enough lifetime in the troposphere which can be easily transported downwind. So emission changes in China will not only change the regional air quality domestically, but also affect the air quality in downwind regions. In this study, we use a global chemistry transport model to simulate the influence on both domestic and foreign air quality from the emission change from 2010 to 2017 in China. By applying the health impact functions derived from epidemiology studies, we then quantify the changes in air pollution-related (including both PM2.5 and O3) mortality burdens at regional and global scales. The majority of air pollutants in China reach their peak values around 2012 and 2013. Compared with the year 2010, the population-weighted annual PM2.5 in China increases till 2011 (94.1 μg m−3), and then begins to decrease. In 2017, the population-weighted annual PM2.5 decreases by 17.6 %, compared with the values in 2010 (84.7 μg m−3). The estimated national PM2.5 concentration changes in China are comparable with previous studies using fine-resolution regional models, though our model tends to overestimate PM2.5 from 2013 to 2017 when evaluated with surface observation in China during the same periods. The emission changes in China increased the global PM2.5-related mortality burdens from 2010 to 2013, by 27,700 (95 %CI: 23,900–31, 400) deaths yr−1 in 2011, and 13, 300 (11,400–15,100) deaths yr−1 in 2013, among which at least 93 % occurred in China. The sharp emission decreases after 2013 bring significant benefits for reduced avoided premature mortality in 2017, reaching 108, 800 (92,800–124,800) deaths yr−1 globally, among which 92 % happening in China. Different trend as PM2.5, the annual maximum daily 8-hr ozone in China increased, and also the ozone-related premature deaths, ranging from 3,600 (2,700–4,300) deaths yr−1 in 2011 (75 % of global total increased premature deaths), and 8,500 (6,500–9,900) deaths yr−1 in 2017 (143 % of the global total). Downwind regions, such as South Korea, Japan, and U.S. generally see a decreased O3-related mortality burden after 2013 as a combination of increased export of ozone and decreased export of ozone precursors. In general, we conclude that the sharp emission reductions in China after 2013 bring benefits of improved air quality and reduced premature deaths associated with air pollution at global scale. The benefits are dominated by the PM2.5 decreases since the ozone is shown to actually increase with the emission decrease.

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High Resolution Chemistry Transport Modeling with the On-Line CHIMERE-WRF Model over the French Alps—Analysis of a Feedback of Surface Particulate Matter Concentrations on Mountain Meteorology

Atmosphere ◽

10.3390/atmos11060565 ◽

2020 ◽

Vol 11 (6) ◽

pp. 565 ◽

Cited By ~ 2

Author(s):

Bertrand Bessagnet ◽

Laurent Menut ◽

Rémy Lapere ◽

Florian Couvidat ◽

Jean-Luc Jaffrezo ◽

...

Keyword(s):

Air Pollution ◽

Particulate Matter ◽

Air Quality ◽

High Altitude ◽

Wrf Model ◽

Synoptic Situation ◽

Modeling Tools ◽

Meteorological Model ◽

French Alps ◽

On Line

Air pollution is of major concern throughout the world and the use of modeling tools to analyze and forecast the pollutant concentrations in complex orographic areas remains challenging. This work proposes an exhaustive framework to analyze the ability of models to simulate the air quality over the French Alps up to 1.2 km resolution over Grenoble and the Arve Valley. The on-line coupled suite of models CHIMERE-WRF is used in its recent version to analyze a 1 month episode in November–December 2013. As expected, an improved resolution increases the concentrations close to the emission areas and reduced the negative bias for Particulate Matter that is the usual weakness of air quality models. However, the nitrate concentrations seem overestimated with at the same time an overestimation of surface temperature in the morning by WRF. Different WRF settings found in the literature are tested to improve the results, particularly the ability of the meteorological model to simulate the strong thermal inversions in the morning. Wood burning is one of the main contributor of air pollution during the period ranging from 80 to 90% of the Organic Matter. The activation of the on-line coupling has a moderate impact on the background concentrations but surprisingly a change of Particulate Matter (PM) concentrations in the valley will affect more the meteorology nearby high altitude areas than in the valley. This phenomenon is the result of a chain of processes involving the radiative effects and the water vapor column gradients in complex orographic areas. At last, the model confirms that the surrounding glaciers are largely impacted by long range transport of desert dust. However, in wintertime some outbreaks of anthropogenic pollution from the valley when the synoptic situation changes can be advected up to the nearby high altitude areas, then deposited.

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Measured and modelled air quality trends in Italy over the period 2003–2010

10.5194/acp-2020-1058 ◽

2021 ◽

Author(s):

Ilaria D'Elia ◽

Gino Briganti ◽

Lina Vitali ◽

Antonio Piersanti ◽

Gaia Righini ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Air Pollutants ◽

Transport Model ◽

Statistical Significance ◽

Average Concentration ◽

Chemical Transport Model ◽

Spatial Coverage ◽

Significant Downward Trend ◽

The Impact

Abstract. Air pollution harms human health and the environment. Several regulatory efforts and different actions have been taken in the last decades by authorities. Air quality trend analysis represents a valid tool in assessing the impact of these actions taken both at national and local levels. This paper presents for the first time the capability of the Italian national chemical transport model, AMS-MINNI, in capturing the observed concentration trends of three air pollutants, NO2, inhalable particles having diameter less than 10 micrometres (PM10) and O3, in Italy over the period 2003–2010. We firstly analyse the model performance finding it in line with the state of the art of regional models applications. The modelled trends result in a general significant downward trend for the three pollutants and, in comparison with observations, the values of the simulated slopes show the same magnitude for NO2 (in the range −3.0 ÷ −0.5 ug m−3 yr−1), while a smaller variability is detected for PM10 (−1.5 ÷ −0.5 ug m−3 yr−1) and O3-maximum daily 8-hour average concentration (−2.0 ÷ −0.5 ug m−3 yr−1). As a general result, we find a good agreement between modelled and observed trends; moreover, the model allowed to extend both the spatial coverage and the statistical significance of pollutants' concentrations trends with respect to observations, in particular for NO2. We also conduct a qualitative attempt to correlate the temporal concentration trends to meteorological and emission variability. Since no clear tendency in yearly meteorological anomalies (temperature, precipitation, geopotential height) was observed for the period investigated, we focus the discussion of concentrations trends on emissions variations. We point out that, due to the complex links between precursors emissions and air pollutants concentrations, emission reductions do not always result in a corresponding decrease in atmospheric concentrations, especially for those pollutants that are formed in the atmosphere such as O3 and the major fraction of PM10. These complex phenomena are still uncertain and their understanding is of the utmost importance in planning future policies for reducing air pollution and its impacts on health and ecosystems.

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The Meteorology-Chemistry Interface Processor (MCIP) for the CMAQ modeling system

Geoscientific Model Development Discussions ◽

10.5194/gmdd-2-1449-2009 ◽

2009 ◽

Vol 2 (2) ◽

pp. 1449-1486 ◽

Cited By ~ 9

Author(s):

T. L. Otte ◽

J. E. Pleim

Keyword(s):

Air Quality ◽

Environmental Protection Agency ◽

Transport Model ◽

Control Strategies ◽

Global Climate ◽

Environmental Modeling ◽

Chemical Transport Model ◽

Meteorological Model ◽

Vertical Coordinate ◽

Regional Air Quality

Abstract. The Community Multiscale Air Quality (CMAQ) modeling system, a state-of-the-science regional air quality modeling system developed by the US Environmental Protection Agency, is being used for a variety of environmental modeling problems including regulatory applications, air quality forecasting, evaluation of emissions control strategies, process-level research, and interactions of global climate change and regional air quality. The Meteorology-Chemistry Interface Processor (MCIP) is a vital piece of software within the CMAQ modeling system that serves to, as best as possible, maintain dynamic consistency between the meteorological model and the chemical transport model. MCIP acts as both a post-processor to the meteorological model and a pre-processor to the CMAQ modeling system. MCIP's functions are to ingest the meteorological model output fields in their native formats, perform horizontal and vertical coordinate transformations, diagnose additional atmospheric fields, define gridding parameters, and prepare the meteorological fields in a form required by the CMAQ modeling system. This paper provides an updated overview of MCIP, documenting the scientific changes that have been made since it was first released as part of the CMAQ modeling system in 1998.

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Comparing Standard to Feature-Based Meteorological Model Evaluation Techniques in Bogotá, Colombia

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-16-0058.1 ◽

2017 ◽

Vol 56 (2) ◽

pp. 391-413 ◽

Cited By ~ 4

Author(s):

Robert Nedbor-Gross ◽

Barron H. Henderson ◽

Justin R. Davis ◽

Jorge E. Pachón ◽

Alexander Rincón ◽

...

Keyword(s):

Air Pollution ◽

Cluster Analysis ◽

Air Quality ◽

Surface Characterization ◽

General Pattern ◽

Model Performance ◽

Specific Humidity ◽

Air Quality Model ◽

Meteorological Model ◽

Feature Based

AbstractStandard meteorological model performance evaluation (sMPE) can be insufficient in determining “fitness” for air quality modeling. An sMPE compares predictions of meteorological variables with community-based thresholds. Conceptually, these thresholds measure the model’s capability to represent mesoscale features that cause variability in air pollution. A method that instead examines features could provide a better estimate of fitness. This work compares measures of fitness from sMPE analysis with a feature-based MPE (fMPE). Meteorological simulations for Bogotá, Colombia, using the Weather Research and Forecasting (WRF) Model provide an ideal case study that highlights the importance of fMPE. Bogotá is particularly interesting because the complex topography presents challenges for WRF in sMPE. A cluster analysis identified four dominant meteorological features associated with air quality driven by wind patterns. The model predictions are able to pass several sMPE thresholds but show poor performance for wind direction. The base simulation can be improved with alternative surface characterization datasets for terrain, soil classification, and land use. Despite doubling the number of days with acceptable specific humidity, overall acceptability was never more than 10%. By comparison, an fMPE showed that predictions were able to reproduce the air-quality-relevant features on 38.4% of the days. The fMPE is based on features derived from an observational cluster analysis that have clear relationships with air quality, which suggests that reproducing those features will indicate better air quality model performance. An fMPE may be particularly useful for high-resolution modeling (1 km or less) when finescale variability can cause poor sMPE performance even when the general pattern that drives air pollution is well reproduced.

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Comparisons of ground-based tropospheric NO<sub>2</sub> MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-5829-2017 ◽

2017 ◽

Vol 17 (9) ◽

pp. 5829-5849 ◽

Cited By ~ 18

Author(s):

Theano Drosoglou ◽

Alkiviadis F. Bais ◽

Irene Zyrichidou ◽

Natalia Kouremeti ◽

Anastasia Poupkou ◽

...

Keyword(s):

Air Quality ◽

Transport Model ◽

Optical Absorption Spectroscopy ◽

Monitoring Site ◽

Air Quality Model ◽

Ozone Monitoring Instrument ◽

Quality Model ◽

Meteorological Model ◽

Tropospheric No2 ◽

Ozone Monitoring

Abstract. One of the main issues arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two data sets. In order to investigate the spatial variability of tropospheric NO2 within a sub-satellite pixel, a campaign which lasted for about 6 months was held in the greater area of Thessaloniki, Greece. Three multi-axial differential optical absorption spectroscopy (MAX-DOAS) systems performed measurements of tropospheric NO2 columns at different sites representative of urban, suburban and rural conditions. The direct comparison of these ground-based measurements with corresponding products from the Ozone Monitoring Instrument onboard NASA's Aura satellite (OMI/Aura) showed good agreement over the rural and suburban areas, while the comparison with the Global Ozone Monitoring Experiment-2 (GOME-2) onboard EUMETSAT's Meteorological Operational satellites' (MetOp-A and MetOp-B) observations is good only over the rural area. GOME-2A and GOME-2B sensors show an average underestimation of tropospheric NO2 over the urban area of about 10.51 ± 8.32  ×  1015 and 10.21 ± 8.87  × 1015 molecules cm−2, respectively. The mean difference between ground-based and OMI observations is significantly lower (6.60 ± 5.71  ×  1015 molecules cm−2). The differences found in the comparisons of MAX-DOAS data with the different satellite sensors can be attributed to the higher spatial resolution of OMI, as well as the different overpass times and NO2 retrieval algorithms of the satellites. OMI data were adjusted using factors calculated by an air quality modeling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multiscale photochemical transport model. This approach resulted in significant improvement of the comparisons over the urban monitoring site. The average difference of OMI observations from MAX-DOAS measurements was reduced to −1.68 ± 5.01  ×  1015 molecules cm−2.

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Association between long term exposure to particulate matter and incident hypertension in Spain

Scientific Reports ◽

10.1038/s41598-021-99154-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Viyey Doulatram-Gamgaram ◽

Sergio Valdés ◽

Cristina Maldonado-Araque ◽

Ana Lago-Sampedro ◽

Rocío Badía-Guillén ◽

...

Keyword(s):

Air Pollution ◽

Particulate Matter ◽

Air Quality ◽

Transport Model ◽

Population Based ◽

Incident Hypertension ◽

Particulate Pollution ◽

Adjusted Model ◽

The Impact

AbstractExposure to air particulate matter has been linked with hypertension and blood pressure levels. The metabolic risks of air pollution could vary according to the specific characteristics of each area, and has not been sufficiently evaluated in Spain. We analyzed 1103 individuals, participants in a Spanish nationwide population based cohort study ([email protected]), who were free of hypertension at baseline (2008–2010) and completed a follow-up exam of the cohort (2016–2017). Cohort participants were assigned air pollution concentrations for particulate matter < 10 μm (PM10) and < 2.5 μm (PM2.5) during follow-up (2008–2016) obtained through modeling combined with measurements taken at air quality stations (CHIMERE chemistry-transport model). Mean and SD concentrations of PM10 and PM2.5 were 20.17 ± 3.91 μg/m3 and 10.83 ± 2.08 μg/m3 respectively. During follow-up 282 cases of incident hypertension were recorded. In the fully adjusted model, compared with the lowest quartile of PM10, the multivariate weighted ORs (95% CIs) for developing hypertension with increasing PM10 exposures were 0.82 (0.59–1.14), 1.28 (0.93–1.78) and 1.45 (1.05–2.01) in quartile 2, 3 and 4 respectively (p for a trend of 0.003). The corresponding weighted ORs according to PM2.5 exposures were 0.80 (0.57–1.13), 1.11 (0.80–1.53) and 1.48 (1.09–2.00) (p for trend 0.004). For each 5-μg/m3 increment in PM10 and PM2.5 concentrations, the odds for incident hypertension increased 1.22 (1.06–1.41) p = 0.007 and 1.39 (1.07–1.81) p = 0.02 respectively. In conclusion, our study contributes to assessing the impact of particulate pollution on the incidence of hypertension in Spain, reinforcing the need for improving air quality as much as possible in order to decrease the risk of cardiometabolic disease in the population.

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Evaluate of air pollution dispersion and propose planing scenerios to reduce air pollution for livestock activities in Tan Thanh district, Ba Ria – Vung Tau province

Science & Technology Development Journal - Science of The Earth & Environment ◽

10.32508/stdjsee.v2i2.491 ◽

2019 ◽

Vol 2 (2) ◽

pp. 26-37 ◽

Cited By ~ 2

Author(s):

Dung Minh Ho ◽

Bang Quoc Ho ◽

Thang Viet Le

Keyword(s):

Air Pollution ◽

Air Quality ◽

Air Pollutants ◽

Agricultural Sector ◽

Ambient Air ◽

Air Quality Model ◽

Quality Model ◽

Meteorological Model ◽

Pollution Dispersion ◽

Air Pollution Dispersion

Livestock is one of the main activities of the agricultural sector in Tan Thanh district, Ba Ria – Vung Tau province. Beside of pollution sources such as waste water, solid waste, livestock activity in Tan Thanh district, Ba Ria - Vung Tau province in recent years has caused air pollution in the livestock area and surrounding area. This research was carried out to evaluate the process of air pollution dispersion from livestock activities based on applying the TAPM meteorological model and AERMOD air quality model. The results showed that the maximum concentrations of air pollutants from livestock area such as NH3, H2S and CH3SH exceeded the National Technical Regulation on Ambient Air Quality (average hour) in the centre of Tan Thanh district, such as Toc Tien commune, part of Tan Phuoc and Phuoc Hoa communes, is 505 μg/m3; 57.4 μg/m3 and 111 μg/m3, respectively. Phu My district and other suburban communes (Hac Dich, Song Xoai, Chau Pha, Tan Hoa, Tan Hai, My Xuan, etc.) have distribution of lower concentrations of air pollutants. Base on the present results of modeling, the authors have proposed livestock development scenarios to control air pollution from this activity, contributing to environmental protection for Tan Thanh district.

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