Spatial distribution and source analysis of SO2 concentration in Urumqi

Li, Shiyao; Xie, Shuguang

doi:10.1016/j.ijhydene.2016.04.142

Cited by 10 publications

(3 citation statements)

References 9 publications

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“…Dandotiya et al ( 2020 ) and Chao et al ( 2021 ) also found an inverse correlation ( r = − 0.38 and r = − 0.34, respectively) between both parameters. Li and Xie ( 2016 ) explained that the inverse relationship between wind speeds and SO 2 concentrations is because lower wind speeds do not promote the diffusion of the pollutant, which results in higher monthly concentrations of SO 2 , while, in conditions with higher wind speeds, the diffusion of SO 2 is favored, so monthly concentration are lower.…”

Section: Resultsmentioning

confidence: 99%

Immission levels and identification of sulfur dioxide sources in La Oroya city, Peruvian Andes

Espinoza-Guillen

Alderete-Malpartida

Cañari-Cancho

et al. 2022

Environ Dev Sustain

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La Oroya is a city in the Peruvian Andes that has suffered a serious deterioration in its air quality, especially due to the high rate of sulfur dioxide (SO 2 ) emissions, which underlines the importance of knowing its sources of contamination and variation over the years. In this sense, this study aimed to evaluate the immission levels and determine the sources of SO 2 contamination in La Oroya. This analysis was performed using the hourly concentration data of SO 2 , and meteorological variables (wind speed and direction), which were analyzed for a period of three years (2018–2020). Graphs of time series, wind and pollutant roses, bivariate polar graphs, clustering k-means, nonparametric statistical tests, and the application of the conditional bivariate probability function were performed to analyze the data and identify the emission sources. The mean concentration of SO 2 was 264.2 μg m −3 for the study period, where 55.66 and 2.37% of the evaluated days exceeded the guideline values recommended by the World Health Organization and the Peruvian Environmental Quality Standard for air for 24 h, respectively. The results showed a defined pattern for the daily and monthly variations, with peaks in the morning hours (0900–1000 h LT) and at the end of the year (December), respectively. The main sources of SO 2 emissions identified were light and heavy vehicles that travel through the Central Highway, the La Oroya Metallurgical Complex, the transit of vehicles within the city, and the diesel–electric locomotives that provide cargo transportation services and tourism passenger transportation. The article attempts to contribute to the development of adequate air quality management policies.

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Section: Resultsmentioning

confidence: 99%

Immission levels and identification of sulfur dioxide sources in La Oroya city, Peruvian Andes

Espinoza-Guillen

Alderete-Malpartida

Cañari-Cancho

et al. 2022

Environ Dev Sustain

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“…Applying CALPUFF, a study on Muscat's (Oman) ISIs revealed winter NO x concentrations surpassing the guidelines set by the United States Environmental Protection Agency (U.S. EPA) [20]. Similarly, in the case of Baosteel Group, a typical steel enterprise in Urumqi, Xinjiang Province, China, CALPUFF identified the highest contribution to the Saybagh high concentration area (SO 2 at 37 µg/m 3 /a) [21]. While these scholars evaluated and ranked air pollutant contributions from ISIs, their assessments often omitted corresponding carbon emissions.…”

Section: Introductionmentioning

confidence: 99%

Improving the Air Quality Management: The Air Pollutant and Carbon Emission and Air Quality Model for Air Pollutant and Carbon Emission Reduction in the Iron and Steel Industries of Tangshan, Hebei Province, China

Chen,

Li,

You

et al. 2023

Atmosphere

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Currently, Tangshan confronts the dual challenge of elevated carbon emissions and substantial pollution discharge from the iron and steel industries (ISIs). While significant efforts have been made to mitigate air pollutants and carbon emissions within the ISIs, there remains a gap in comprehending the control of carbon emissions, air pollutant emissions, and their contributions to air pollutant concentrations at the enterprise level. In this study, we devised the Air Pollutant and Carbon Emission and Air Quality (ACEA) model to identify enterprises with noteworthy air pollution and carbon emissions, as well as substantial contributions to air pollutant concentrations. We constructed a detailed inventory of air pollutants and CO2 emissions from the iron and steel industry in Tangshan for the year 2019. The findings reveal that in 2019, Tangshan emitted 5.75 × 104 t of SO2, 13.47 × 104 t of NOx, 3.55 × 104 t of PM10, 1.80 × 104 t of PM2.5, 5.79 × 106 t of CO and 219.62 Mt of CO2. The ACEA model effectively pinpointed key links between ISI enterprises emitting air pollutants and carbon dioxide, notably in pre-iron-making processes (coking, sintering, pelletizing) and the Blast furnace. By utilizing the developed air pollutant emission inventory, the CALPUFF model assessed the impact of ISI enterprises on air quality in the Tangshan region. Subsequently, we graded the performance of air pollutant and CO2 emissions following established criteria. The ACEA model successfully identified eight enterprises with significant air pollution and carbon emissions, exerting notable influence on air pollutant concentrations. Furthermore, the ACEA outcomes offer the potential for enhancing regional air quality in Tangshan and provide a scientific instrument for mitigating air pollutants and carbon emissions. The effective application of the ACEA model in Tangshan’s steel industry holds promise for supporting carbon reduction initiatives and elevating environmental standards in other industrial cities across China.

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“…The model is a three-dimensional transient Lagrange dispersion model system [24][25][26], which can be applied to simulate the transient diffusion, transport, and transformation of gases, particles, and other pollutants (such as PM 2.5 , SO 2 , NO X , etc.) derived by various meteorological factors [27][28][29]. The CALPUFF atmospheric dispersion model system consists of the CALMET (a diagnostic 3-D meteorological model) meteorological module [30,31], the CALPUFF plume transport module, the CALPOST (California puff post-processing model) post-processing module [32,33], and modules for pre-processing conventional ground station meteorological data, geographic data, altitude data, and precipitation data.…”

Section: Model Introduction and Parametersmentioning

confidence: 99%

Atmospheric Pollution Impact Assessment of Brick and Tile Industry: A Case Study of Xinmi City in Zhengzhou, China

Xie

2021

Sustainability

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The brick and tile industry was selected to investigate the impact of pollutants emitted from such industry on air quality. Based on the 2018 Zhengzhou City Census data and combined with field sampling and research visits, an emission inventory of the brick and tile industry in Xinmi City was established using the emission factor method. Based on the established emission inventory, the concentrations of SO2, NOX, and PM2.5 emitted by 31 brick and tile enterprises were then predicted using the CALPUFF model(California puff model, USEPA), which had been evaluated for accuracy, and the simulation results were compared with the observed results to obtain the impact of pollutant emissions from the brick and tile industry on air pollution in the simulated region. Results show that SO2, NOX, and PM2.5 emissions from the brick and tile industry in the study area in 2018 were 564.86 tons, 513.16 tons, and 41.01 tons, respectively. The CALPUFF model can simulate the characteristics of meteorological changes and pollutant concentration trends, and the correlation coefficient of the fit curve between the pollutant observed data and the simulated data was higher than 0.8, which can reproduce the impact of key industrial point sources on air quality well. The simulated concentration values and spatial and temporal distribution characteristics of SO2, NOX, PM2.5 in spring, summer, autumn, and winter were obtained from the model simulations. The contribution of pollutant emissions from the brick and tile industry to the monthly average concentrations of SO2, NOX, and PM2.5 in the simulated region were 6.58%, 5.38%, and 1.42%, respectively, with the Housing Administration monitoring station as the receptor point. The brick and tile industry should increase the emission control measures of SO2 and NOX, and at the same time, the emission control of PM2.5 cannot be slackened.

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Spatial distribution and source analysis of SO2 concentration in Urumqi

Cited by 10 publications

References 9 publications

Immission levels and identification of sulfur dioxide sources in La Oroya city, Peruvian Andes

Immission levels and identification of sulfur dioxide sources in La Oroya city, Peruvian Andes

Improving the Air Quality Management: The Air Pollutant and Carbon Emission and Air Quality Model for Air Pollutant and Carbon Emission Reduction in the Iron and Steel Industries of Tangshan, Hebei Province, China

Atmospheric Pollution Impact Assessment of Brick and Tile Industry: A Case Study of Xinmi City in Zhengzhou, China

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