Evaluation of low wind modeling approaches for two tall-stack databases

<div><p>The performance of the AERMOD air dispersion model under low wind speed conditions, especially for applications with only one level of meteorological data and no direct turbulence measurements or vertical temperature gradient observations, is the focus of this study. The analysis documented in this paper addresses evaluations for low wind conditions involving tall stack releases for which multiple years of concurrent emissions, meteorological data, and monitoring data are available. AERMOD was tested on two field-study databases involving several SO₂ monitors and hourly emissions data that had sub-hourly meteorological data (e.g., 10-min averages) available using several technical options: default mode, with various low wind speed beta options, and using the available sub-hourly meteorological data. These field study databases included (1) Mercer County, a North Dakota database featuring five SO₂ monitors within 10 km of the Dakota Gasification Company’s plant and the Antelope Valley Station power plant in an area of both flat and elevated terrain, and (2) a flat-terrain setting database with four SO₂ monitors within 6 km of the Gibson Generating Station in southwest Indiana. Both sites featured regionally representative 10-m meteorological databases, with no significant terrain obstacles between the meteorological site and the emission sources. The low wind beta options show improvement in model performance helping to reduce some of the overprediction biases currently present in AERMOD when run with regulatory default options. The overall findings with the low wind speed testing on these tall stack field-study databases indicate that AERMOD low wind speed options have a minor effect for flat terrain locations, but can have a significant effect for elevated terrain locations. The performance of AERMOD using low wind speed options leads to improved consistency of meteorological conditions associated with the highest observed and predicted concentration events. The available sub-hourly modeling results using the Sub-Hourly AERMOD Run Procedure (SHARP) are relatively unbiased and show that this alternative approach should be seriously considered to address situations dominated by low-wind meander conditions.</p><p>Implications: <i>AERMOD was evaluated with two tall stack databases (in North Dakota and Indiana) in areas of both flat and elevated terrain. AERMOD cases included the regulatory default mode, low wind speed beta options, and use of the Sub-Hourly AERMOD Run Procedure (SHARP). The low wind beta options show improvement in model performance (especially in higher terrain areas), helping to reduce some of the overprediction biases currently present in regulatory default AERMOD. The SHARP results are relatively unbiased and show that this approach should be seriously considered to address situations dominated by low-wind meander conditions.</i></p></div

Effects of fuel components and combustion particle physicochemical properties on toxicological responses of lung cells

<p>The physicochemical properties of combustion particles that promote lung toxicity are not fully understood, hindered by the fact that combustion particles vary based on the fuel and combustion conditions. Real-world combustion-particle properties also continually change as new fuels are implemented, engines age, and engine technologies evolve. This work used laboratory-generated particles produced under controlled combustion conditions in an effort to understand the relationship between different particle properties and the activation of established toxicological outcomes in human lung cells (H441 and THP-1). Particles were generated from controlled combustion of two simple biofuel/diesel surrogates (methyl decanoate and dodecane/biofuel-blended diesel (BD), and butanol and dodecane/alcohol-blended diesel (AD)) and compared to a widely studied reference diesel (RD) particle (NIST SRM2975/RD). BD, AD, and RD particles exhibited differences in size, surface area, extractable chemical mass, and the content of individual polycyclic aromatic hydrocarbons (PAHs). Some of these differences were directly associated with different effects on biological responses. BD particles had the greatest surface area, amount of extractable material, and oxidizing potential. These particles and extracts induced cytochrome P450 1A1 and 1B1 enzyme mRNA in lung cells. AD particles and extracts had the greatest total PAH content and also caused CYP1A1 and 1B1 mRNA induction. The RD extract contained the highest relative concentration of 2-ring PAHs and stimulated the greatest level of interleukin-8 (IL-8) and tumor necrosis factor-alpha (TNFα) cytokine secretion. Finally, AD and RD were more potent activators of TRPA1 than BD, and while neither the TRPA1 antagonist HC-030031 nor the antioxidant N-acetylcysteine (NAC) affected CYP1A1 or 1B1 mRNA induction, both inhibitors reduced IL-8 secretion and mRNA induction. These results highlight that differences in fuel and combustion conditions affect the physicochemical properties of particles, and these differences, in turn, affect commonly studied biological/toxicological responses.</p

Additional file 1: of Genome-wide association study of lung function and clinical implication in heavy smokers

Table S1. Association Results of the Top SNPs (P < 10− 4) with Post-bronchodilator FEV1/FVC. Table S2. Association Results of the Top SNPs (P < 10− 4) with Post-bronchodilator % Predicted FEV1.Table S3. Genotype Frequency of rs28929474 in SERPINA1 Stratified by GOLD Stages. Table S4. Prediction Models for Post-bronchodilator Lung Function Using Top 10 SNPs for Post-bronchodilator % Predicted FEV1.Figure S1. Joint analysis of the top10 SNPs for post-bronchodilator % predicted FEV1 in 1075 SPIROMICS non-Hispanic White smokers with COPD. (DOCX 141 kb