Persistence of initial conditions in continental scale air quality simulations

Origin of regional springtime ozone episodes in the Sichuan Basin, China: Role of synoptic forcing and regional transport

The Sichuan Basin (SCB) located in southwestern China has long been considered the most polluted city cluster with exposure to unhealthy levels of ozone (O₃) at times. However, the features of O₃ regional transport and source contributions in SCB are poorly understood. In this study, ambient measurements, ERA5 reanalysis dataset, IASI O₃ column, and the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) modeling system coupled with the Integrated Source Apportionment Method (ISAM) module were used to investigate the formation mechanism and sources of a severe O₃ episode in spring 2020 over the SCB. In the first stage of the O₃ episode, a high-pressure system persisted over the western SCB and caused northeasterly wind fields, leading to enhanced regional transport from the northern boundary with the O₃ contribution from the boundary exceeding 50% across the SCB. As the synoptic pattern evolved, southeasterly winds dominated the SCB and the stagnant zone over the Chengdu Plain confined O₃ originating from the southern SCB and Chongqing city, leading to the accumulation of precursors and elevated O₃ levels. During the O₃ episode, transportation and industrial sources were major contributors to O₃ formation especially for the Chengdu Plain and Chongqing city. In addition, the O₃-rich air mass in the nocturnal residual layer that formed over Chongqing city was transported to the Chengdu Plain through southeastern corridor at 400-1600m above ground-level under the prevailing southeasterly winds. With sunrise and the development of the atmospheric boundary layer, the O₃-rich air mass in the residual layer (RL) was entrained to the ground-level via vertical mixing, which further enhanced O₃ pollution across the Chengdu Plain. Our results revealed the mechanism of regional transport via northeastern and southeastern corridors during an O₃ episode and demonstrated the need for joint emission regulation across the SCB to mitigate O₃ pollution.

Top-down vehicle emission inventory for spatial distribution and dispersion modeling of particulate matter

Emission inventories are one of the most critical inputs for the successful modeling of air quality. The performance of the modeling results is directly affected by the quality of atmospheric emission inventories. Consequently, the development of representative inventories is always required. Due to the lack of regional inventories in Brazil, this study aimed to investigate the use of the particulate matter (PM) emission estimation from the Brazilian top-down vehicle emission inventory (VEI) of 2012 for air quality modeling. Here, we focus on road vehicles since they are usually responsible for significant emissions of PM in urban areas. The total Brazilian emission of PM (63,000 t year^-1) from vehicular sources was distributed into the urban areas of 5557 municipalities, with 1-km² grid spacing, considering two approaches: (i) population and (ii) fleet of each city. A comparison with some local inventories is discussed. The inventory was compiled in the PREP-CHEM-SRC processor tool. One-month modeling (August 2015) was performed with WRF-Chem for the four metropolitan areas of Brazilian Southeast: Belo Horizonte (MABH), Great Vitória (MAGV), Rio de Janeiro (MARJ), and São Paulo (MASP). In addition, modeling with the Emission Database for Global Atmospheric Research (EDGAR) inventory was carried out to compare the results. Overall, EDGAR inventory obtained higher PM emissions than the VEI segregated by population and fleet, which is expected owing to considerations of additional sources of emission (e.g., industrial and residential). This higher emission of EDGAR resulted in higher PM₁₀ and PM_2.5 concentrations, overestimating the observations in MASP, while the proposed inventory well represented the ambient concentrations, obtaining better statistics indices. For the other three metropolitan areas, both EDGAR and the VEI inventories obtained consistent results. Therefore, the present work endorses the fact that vehicles are responsible for the more substantial contribution to PM emissions in the studied urban areas. Furthermore, the use of VEI can be representative for modeling air quality in the future.

Quantifying the impact of particle matter on mortality and hospitalizations in four Brazilian metropolitan areas

Air quality management involves investigating areas where pollutant concentrations are above guideline or standard values to minimize its effect on human health. Particulate matter (PM) is one of the most studied pollutants, and its relationship with health has been widely outlined. To guide the construction and improvement of air quality policies, the impact of PM on the four Brazilian southeast metropolitan areas was investigated. One-year long modeling of PM₁₀ and PM_2.5 was performed with the WRF-Chem model for 2015 to quantify daily and annual PM concentrations in 102 cities. Avoidable mortality due to diverse causes and morbidity due to respiratory and circular system diseases were estimated concerning WHO guidelines, which was adopted in Brazil as a final standard to be reached in the future; although there is no deadline set for its implementation yet. Results showed satisfactory representation of meteorology and ambient PM concentrations. An overestimation in PM concentrations for some monitoring stations was observed, mainly in São Paulo metropolitan area. Cities around capitals with high modelled annual PM_2.5 concentrations do not monitor this pollutant. The total avoidable deaths estimated for the region, related to PM_2.5, were 32,000 ± 5,300 due to all-cause mortality, between 16,000 ± 2,100 and 51,000 ± 3,000 due non-accidental causes, between 7,300 ± 1,300 and 16,700 ± 1,500 due to cardiovascular disease, between 4,750 ± 900 and 10,950 ± 870 due ischemic heart diseases and 1,220 ± 330 avoidable deaths due to lung cancer. Avoidable respiratory hospitalizations were greater for PM_2.5 among 'children' age group than for PM₁₀ (all age group) except in São Paulo metropolitan area. For circulatory system diseases, 9,840 ± 3,950 avoidable hospitalizations in the elderly related to a decrease in PM_2.5 concentrations were estimated. This study endorses that more restrictive air quality standards, human exposure, and health effects are essential factors to consider in urban air quality management.

New Bidirectional Ammonia Flux Model in an Air Quality Model Coupled With an Agricultural Model

Ammonia surface flux is bidirectional; that is, net flux can be either upward or downward. In fertilized agricultural croplands and grasslands there is usually more emission than deposition especially in midday during warmer seasons. In North America, most of the ammonia emissions are from agriculture with a significant fraction of that coming from fertilizer. A new bidirectional ammonia flux modeling system has been developed in the Community Multiscale Air Quality (CMAQ) model, which has close linkages with the Environmental Policy Integrated Climate (EPIC) agricultural ecosystem model. Daily inputs from EPIC are used to calculate soil ammonia concentrations that are combined with air concentrations in CMAQ to calculate bidirectional surface flux. The model is evaluated against surface measurements of NH₃ concentrations, NH₄ ⁺ and SO₄ ^2- aerosol concentrations, NH₄ ⁺ wet deposition measurements, and satellite retrievals of NH₃ concentrations. The evaluation shows significant improvement over the base model without bidirectional ammonia flux. Comparisons to monthly average satellite retrievals show similar spatial distribution with the highest ammonia concentrations in the Central Valley of California (CA), the Snake River valley in Idaho, and the western High Plains. In most areas the model underestimates, but in the Central Valley of CA, it generally overestimates ammonia concentration. Case study analyses indicate that modeled high fluxes of ammonia in CA are often caused by anomalous high soil ammonia loading from EPIC for particular crop types. While further improvements to parameterizations in EPIC and CMAQ are recommended, this system is a significant advance over previous ammonia bidirectional surface flux models.

Characterization and source apportionment of marine aerosols over the East China Sea

Awareness of the importance of marine atmosphere for accurately estimating global aerosol budget and climate impacts has arisen recently. However, studies are limited due to the difficulty and inconvenience in sampling as well as the diversity of sources. In this study, the Community Multiscale Air Quality (CMAQ) model was applied to investigate the fine particulate matter (PM_2.5) and its chemical components over the East China Sea (ECS) and offshore regions. In spite of slight under-predictions, model predictions agree well with observations over the ECS and along the coast. PM_2.5 and its major components in the mainland are higher than in marine area, suggesting Asian continent is a major emitter of marine aerosols. PM_2.5 and its components in marine regions show higher abundance during daytime than nighttime, while it is opposite in continental regions. Aerosol phase SO₄^2- is the most abundant component of PM_2.5 over the ECS with an average concentration of 5.12 μg m^-3, followed by NH₄⁺ (1.02 μg m^-3) and primary organic aerosol (POA) (0.92 μg m^-3). Industry and ship emissions are the top two contributors to primary (PPM) and total PM_2.5 over the ECS, while industry and agriculture sectors are major sources for secondary inorganic aerosols (SIA), followed by ship emissions. For terrestrial regions, industry and agriculture are predominant sources of PM_2.5 and SIA, while industry and residential activities are the top two contributors to PPM. This study improves the understanding of transport and accumulation of air pollutants over the ECS and adjacent regions, and provides useful information for designing efficient control strategies.

WRF-SMOKE-CMAQ modeling system for air quality evaluation in São Paulo megacity with a 2008 experimental campaign data

Atmospheric pollutants are strongly affected by transport processes and chemical transformations that alter their composition and the level of contamination in a region. In the last decade, several studies have employed numerical modeling to analyze atmospheric pollutants. The objective of this study is to evaluate the performance of the WRF-SMOKE-CMAQ modeling system to represent meteorological and air quality conditions over São Paulo, Brazil, where vehicular emissions are the primary contributors to air pollution. Meteorological fields were modeled using the Weather Research and Forecasting model (WRF), for a 12-day period during the winter of 2008 (Aug. 10th-Aug. 22nd), using three nested domains with 27-km, 9-km, and 3-km grid resolutions, which covered the most polluted cities in São Paulo state. The 3-km domain was aligned with the Sparse Matrix Operator Kernel Emissions (SMOKE), which processes the emission inventory for the Models-3 Community Multiscale Air Quality Modeling System (CMAQ). Data from an aerosol sampling campaign was used to evaluate the modeling. The PM₁₀ and ozone average concentration of the entire period was well represented, with correlation coefficients for PM₁₀, varying from 0.09 in Pinheiros to 0.69 in ICB/USP, while for ozone, the correlation coefficients varied from 0.56 in Pinheiros to 0.67 in IPEN. However, the model underestimated the concentrations of PM_2.5 during the experiment, but with ammonium showing small differences between predicted and observed concentrations. As the meteorological model WRF underestimated the rainfall and overestimated the wind speed, the accuracy of the air quality model was expected to be below the desired value. However, in general, the CMAQ model reproduced the behavior of atmospheric aerosol and ozone in the urban area of São Paulo.

Impacts of different characterizations of large-scale background on simulated regional-scale ozone over the continental United States

This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boundary conditions derived from hemispheric or global-scale models. The Community Multiscale Air Quality (CMAQ) model simulations supporting this analysis were performed over the continental US for the year 2010 within the context of the Air Quality Model Evaluation International Initiative (AQMEII) and Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) activities. CMAQ process analysis (PA) results highlight the dominant role of horizontal and vertical advection on the ozone burden in the mid-to-upper troposphere and lower stratosphere. Vertical mixing, including mixing by convective clouds, couples fluctuations in free-tropospheric ozone to ozone in lower layers. Hypothetical bounding scenarios were performed to quantify the effects of emissions, boundary conditions, and ozone dry deposition on the simulated ozone burden. Analysis of these simulations confirms that the characterization of ozone outside the regional-scale modeling domain can have a profound impact on simulated regional-scale ozone. This was further investigated by using data from four hemispheric or global modeling systems (Chemistry - Integrated Forecasting Model (C-IFS), CMAQ extended for hemispheric applications (H-CMAQ), the Goddard Earth Observing System model coupled to chemistry (GEOS-Chem), and AM3) to derive alternate boundary conditions for the regional-scale CMAQ simulations. The regional-scale CMAQ simulations using these four different boundary conditions showed that the largest ozone abundance in the upper layers was simulated when using boundary conditions from GEOS-Chem, followed by the simulations using C-IFS, AM3, and H-CMAQ boundary conditions, consistent with the analysis of the ozone fields from the global models along the CMAQ boundaries. Using boundary conditions from AM3 yielded higher springtime ozone columns burdens in the middle and lower troposphere compared to boundary conditions from the other models. For surface ozone, the differences between the AM3-driven CMAQ simulations and the CMAQ simulations driven by other large-scale models are especially pronounced during spring and winter where they can reach more than 10 ppb for seasonal mean ozone mixing ratios and as much as 15 ppb for domain-averaged daily maximum 8 h average ozone on individual days. In contrast, the differences between the C-IFS-, GEOS-Chem-, and H-CMAQ-driven regional-scale CMAQ simulations are typically smaller. Comparing simulated sur face ozone mixing ratios to observations and computing seasonal and regional model performance statistics revealed that boundary conditions can have a substantial impact on model performance. Further analysis showed that boundary conditions can affect model performance across the entire range of the observed distribution, although the impacts tend to be lower during summer and for the very highest observed percentiles. The results are discussed in the context of future model development and analysis opportunities.

Source apportionment of PM2.5 in North India using source-oriented air quality models

In recent years, severe pollution events were observed frequently in India especially at its capital, New Delhi. However, limited studies have been conducted to understand the sources to high pollutant concentrations for designing effective control strategies. In this work, source-oriented versions of the Community Multi-scale Air Quality (CMAQ) model with Emissions Database for Global Atmospheric Research (EDGAR) were applied to quantify the contributions of eight source types (energy, industry, residential, on-road, off-road, agriculture, open burning and dust) to fine particulate matter (PM_2.5) and its components including primary PM (PPM) and secondary inorganic aerosol (SIA) i.e. sulfate, nitrate and ammonium ions, in Delhi and three surrounding cities, Chandigarh, Lucknow and Jaipur in 2015. PPM mass is dominated by industry and residential activities (>60%). Energy (∼39%) and industry (∼45%) sectors contribute significantly to PPM at south of Delhi, which reach a maximum of 200 μg/m³ during winter. Unlike PPM, SIA concentrations from different sources are more heterogeneous. High SIA concentrations (∼25 μg/m³) at south Delhi and central Uttar Pradesh were mainly attributed to energy, industry and residential sectors. Agriculture is more important for SIA than PPM and contributions of on-road and open burning to SIA are also higher than to PPM. Residential sector contributes highest to total PM_2.5 (∼80 μg/m³), followed by industry (∼70 μg/m³) in North India. Energy and agriculture contribute ∼25 μg/m³ and ∼16 μg/m³ to total PM_2.5, while SOA contributes <5 μg/m³. In Delhi, industry and residential activities contribute to 80% of total PM_2.5.

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9-12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed ~1.3% (mean, min-max: 0.46, 0.3-0.5 ppbv) and 0.2% (0.013, 0.004-0.02 μg/m³) of total O₃ and PM_2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O₃ 0.69, 0.5-0.85 ppbv) and 0.5% (PM_2.5 0.03, 0.01-0.05 μg/m³)) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km²) and fine (36 × 36 km²) grid resolutions in NA showed ~70 times and ~13 times higher aviation impacts for O₃ and PM_2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions.