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Man X, Liu R, Zhang Y, Yu W, Kong F, Liu L, Luo Y, Feng T. High-spatial resolution ground-level ozone in Yunnan, China: A spatiotemporal estimation based on comparative analyses of machine learning models. ENVIRONMENTAL RESEARCH 2024; 251:118609. [PMID: 38442812 DOI: 10.1016/j.envres.2024.118609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Revised: 02/07/2024] [Accepted: 02/29/2024] [Indexed: 03/07/2024]
Abstract
Monitoring ground-level ozone concentrations is a critical aspect of atmospheric environmental studies. Given the existing limitations of satellite data products, especially the lack of ground-level ozone characterization, and the discontinuity of ground observations, there is a pressing need for high-precision models to simulate ground-level ozone to assess surface ozone pollution. In this study, we have compared several widely utilized ensemble learning and deep learning methods for ground-level ozone simulation. Furthermore, we have thoroughly contrasted the temporal and spatial generalization performances of the ensemble learning and deep learning models. The 3-Dimensional Convolutional Neural Network (3-D CNN) model has emerged as the optimal choice for evaluating the daily maximum 8-h average ozone in Yunnan Province. The model has good performance: a spatial resolution of 0.05° × 0.05° and strong predictive power, as indicated by a Coefficient of Determination (R2) of 0.83 and a Root Mean Square Error (RMSE) of 12.54 μg/m³ in sample-based 5-fold cross-validation (CV). In the final stage of our study, we applied the 3-D CNN model to generate a comprehensive daily maximum 8-h average ozone dataset for Yunnan Province for the year 2021. This application has furnished us with a crucial high-resolution and highly accurate dataset for further in-depth studies on the issue of ozone pollution in Yunnan Province.
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Affiliation(s)
- Xingwei Man
- School of Earth Sciences, Yunnan University, Kunming, Yunnan, 650504, PR China
| | - Rui Liu
- School of Earth Sciences, Yunnan University, Kunming, Yunnan, 650504, PR China.
| | - Yu Zhang
- School of Earth Sciences, Yunnan University, Kunming, Yunnan, 650504, PR China
| | - Weiqiang Yu
- School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, Yunnan, 650221, PR China
| | - Fanhao Kong
- School of Earth Sciences, Yunnan University, Kunming, Yunnan, 650504, PR China
| | - Li Liu
- Institute of International Rivers and Eco-Security, Yunnan University, Kunming, Yunnan, 650504, PR China
| | - Yan Luo
- School of Earth Sciences, Yunnan University, Kunming, Yunnan, 650504, PR China
| | - Tao Feng
- School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, Yunnan, 650221, PR China.
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Yavaş M, Dursun D, Toy S. Simulating the effect of urban sprawl on air quality and outdoor human thermal comfort in a cold city, Erzurum, Turkey. ENVIRONMENTAL MONITORING AND ASSESSMENT 2023; 195:1276. [PMID: 37801252 DOI: 10.1007/s10661-023-11897-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 09/26/2023] [Indexed: 10/07/2023]
Abstract
Research on climate-sensitive urban planning is important to improve the quality of city life. Cold climate cities should respect climatic characteristics to diversify outdoor uses and increase air quality to maximize the benefits of winter. This study is aimed to explore the impact of changing urban pattern on air pollution and outdoor human thermal comfort conditions (HTCCs) in a newly developed urban area in Şükrüpaşa neighbourhood, Erzurum, among the coldest cities in Turkey, with high PM10 and low HTCCs levels. Sensitivity of urban development pattern to climate conditions and its suitability to eliminate the winter disturbances caused by HTCCs and air pollution were investigated by producing maps for HTCCs and air pollution using morphological, meteorological and spatial data and ENVI-met model in winter period of 2017 and 2022. It was found that newly developed areas increase the unfavourable conditions in terms of air quality, temperature and HTCCs due to the reasons like improper land uses, urban sprawl, high urban density and ventilation problems. In high-elevated cold cities, spatial planning and design principles should strictly be followed by incorporating climate knowledge and without revising the spatial decisions.
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Affiliation(s)
- Merve Yavaş
- Department of City and Regional Planning, Faculty of Architecture and Design, Atatürk University, Erzurum, Turkey
| | - Doğan Dursun
- Department of City and Regional Planning, Faculty of Architecture and Design, Atatürk University, Erzurum, Turkey
| | - Süleyman Toy
- Department of City and Regional Planning, Faculty of Architecture and Design, Atatürk University, Erzurum, Turkey.
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Sadeghi B, Ghahremanloo M, Mousavinezhad S, Lops Y, Pouyaei A, Choi Y. Contributions of meteorology to ozone variations: Application of deep learning and the Kolmogorov-Zurbenko filter. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 310:119863. [PMID: 35963387 DOI: 10.1016/j.envpol.2022.119863] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 07/07/2022] [Accepted: 07/23/2022] [Indexed: 06/15/2023]
Abstract
From hourly ozone observations obtained from three regions⸻Houston, Dallas, and West Texas⸻we investigated the contributions of meteorology to changes in surface daily maximum 8-h average (MDA8) ozone from 2000 to 2019. We applied a deep convolutional neural network and Shapely additive explanation (SHAP) to examine the complex underlying nonlinearity between variations of surface ozone and meteorological factors. Results of the models showed that between 2000 and 2019, specific humidity (38% and 27%) and temperature (28% and 37%) contributed the most to ozone formation over the Houston and Dallas metropolitan areas, respectively. On the other hand, the results show that solar radiation (50%) strongly impacted ozone variation over West Texas during this time. Using a combination of the Kolmogorov-Zurbenko (KZ) filter and multiple linear regression, we also evaluated the influence of meteorology on ozone and quantified the contributions of meteorological parameters to trends in surface ozone formation. Our findings showed that in Houston and Dallas, meteorology influenced ozone variations to a large extent. The impacts of meteorology on West Texas, however, showed meteorological factors had fewer influences on ozone variabilities from 2000 to 2019. This study showed that SHAP analysis and the KZ approach can investigate the contributions of the meteorological factors on ozone concentrations and help policymakers enact effective ozone mitigation policies.
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Affiliation(s)
- Bavand Sadeghi
- Department of Earth and Atmospheric Science, University of Houston, Texas, USA
| | - Masoud Ghahremanloo
- Department of Earth and Atmospheric Science, University of Houston, Texas, USA
| | | | - Yannic Lops
- Department of Earth and Atmospheric Science, University of Houston, Texas, USA
| | - Arman Pouyaei
- Department of Earth and Atmospheric Science, University of Houston, Texas, USA
| | - Yunsoo Choi
- Department of Earth and Atmospheric Science, University of Houston, Texas, USA.
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Impact of Climate-Driven Land-Use Change on O3 and PM Pollution by Driving BVOC Emissions in China in 2050. ATMOSPHERE 2022. [DOI: 10.3390/atmos13071086] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
This study predicted three future land-use type scenarios in 2050 (including the Shared Socioeconomic Pathway SSP126, SSP585, and carbon scenario) based on the Land-Use Harmonization (LUH2) project and the future evolution of land-use types considering China’s carbon neutrality background. The contribution of land-use changes to terrestrial natural source biogenic volatile organic compounds (BVOCs), as well as O3 and PM concentrations, were determined. Under the SSP126 pathway, meteorological changes would increase BVOC emissions in China by 1.0 TgC in 2050, compared with 2015, while land-use changes would increase them by 1.5–7.1 TgC. The impact of land-use changes on O3 and PM concentrations would be less than 3.6% in 2050 and greater in summer. Regional differences must be considered when calculating future environmental background concentrations of pollutants. Due to more afforestation measures under the SSP126 scenario, the impact of land-use change on pollutants was more obvious under the SSP126 pathway than under the SSP585 pathway. Under the carbon scenario, the increase in PM concentration caused by land-use changes would pose a risk to air quality compliance; thus, it is necessary to consider reducing or offsetting this potential risk through anthropogenic emission control measures.
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Abstract
The USGS (United States Geological Survey) land-use data used in the Weather Research and Forecasting (WRF) model have become obsolete as they are unable to accurately represent actual underlying surface features. Therefore, this study developed a new multi-satellite remote-sensing land-use dataset based on the latest GLC2015 (Global Land Cover, 2015) land-use data, which had 300 m spatial resolution. The new data were used to update the default USGS land-use dataset. Based on observational data from national meteorological observing stations in Xinjiang, northwest China, a comparison of the old USGS and new GLC2015 land-use datasets in the WRF model was performed for July 2018, where the simulated variables included the sensible heat flux (SHF), latent heat flux (LHF), surface skin temperature (Tsk), two-meter air temperature (T2), wind speed (Winds), specific humidity (Q2) and relative humidity (RH). The results indicated that there were significant differences between the two datasets. For example, our statistical verification results found via in situ observations made by the MET (model evaluation tools) illustrated that the bias of T2 decreased by 2.54%, the root mean square error (RMSE) decreased by 1.48%, the bias of Winds decreased by 10.46%, and the RMSE decreased by 6.77% when using the new dataset, and the new parameter values performed a net positive effect on land–atmosphere interactions. These results suggested that the GLC2015 land-use dataset developed in this study was useful in terms of improving the performance of the WRF model in the summer months.
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Urban Heat Island Simulations in Guangzhou, China, Using the Coupled WRF/UCM Model with a Land Use Map Extracted from Remote Sensing Data. SUSTAINABILITY 2016. [DOI: 10.3390/su8070628] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Pusede SE, Steiner AL, Cohen RC. Temperature and recent trends in the chemistry of continental surface ozone. Chem Rev 2015; 115:3898-918. [PMID: 25950502 DOI: 10.1021/cr5006815] [Citation(s) in RCA: 117] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
| | - Allison L Steiner
- §Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, Michigan 48109, United States
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Reforestation as a novel abatement and compliance measure for ground-level ozone. Proc Natl Acad Sci U S A 2014; 111:E4204-13. [PMID: 25201970 DOI: 10.1073/pnas.1409785111] [Citation(s) in RCA: 63] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
High ambient ozone (O3) concentrations are a widespread and persistent problem globally. Although studies have documented the role of forests in removing O3 and one of its precursors, nitrogen dioxide (NO2), the cost effectiveness of using peri-urban reforestation for O3 abatement purposes has not been examined. We develop a methodology that uses available air quality and meteorological data and simplified forest structure growth-mortality and dry deposition models to assess the performance of reforestation for O3 precursor abatement. We apply this methodology to identify the cost-effective design for a hypothetical 405-ha, peri-urban reforestation project in the Houston-Galveston-Brazoria O3 nonattainment area in Texas. The project would remove an estimated 310 tons of (t) O3 and 58 t NO2 total over 30 y. Given its location in a nitrogen oxide (NOx)-limited area, and using the range of Houston area O3 production efficiencies to convert forest O3 removal to its NOx equivalent, this is equivalent to 127-209 t of the regulated NOx. The cost of reforestation per ton of NOx abated compares favorably to that of additional conventional controls if no land costs are incurred, especially if carbon offsets are generated. Purchasing agricultural lands for reforestation removes this cost advantage, but this problem could be overcome through cost-share opportunities that exist due to the public and conservation benefits of reforestation. Our findings suggest that peri-urban reforestation should be considered in O3 control efforts in Houston, other US nonattainment areas, and areas with O3 pollution problems in other countries, wherever O3 formation is predominantly NOx limited.
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Fiore AM, Naik V, Spracklen DV, Steiner A, Unger N, Prather M, Bergmann D, Cameron-Smith PJ, Cionni I, Collins WJ, Dalsøren S, Eyring V, Folberth GA, Ginoux P, Horowitz LW, Josse B, Lamarque JF, MacKenzie IA, Nagashima T, O'Connor FM, Righi M, Rumbold ST, Shindell DT, Skeie RB, Sudo K, Szopa S, Takemura T, Zeng G. Global air quality and climate. Chem Soc Rev 2012; 41:6663-83. [PMID: 22868337 DOI: 10.1039/c2cs35095e] [Citation(s) in RCA: 113] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Emissions of air pollutants and their precursors determine regional air quality and can alter climate. Climate change can perturb the long-range transport, chemical processing, and local meteorology that influence air pollution. We review the implications of projected changes in methane (CH(4)), ozone precursors (O(3)), and aerosols for climate (expressed in terms of the radiative forcing metric or changes in global surface temperature) and hemispheric-to-continental scale air quality. Reducing the O(3) precursor CH(4) would slow near-term warming by decreasing both CH(4) and tropospheric O(3). Uncertainty remains as to the net climate forcing from anthropogenic nitrogen oxide (NO(x)) emissions, which increase tropospheric O(3) (warming) but also increase aerosols and decrease CH(4) (both cooling). Anthropogenic emissions of carbon monoxide (CO) and non-CH(4) volatile organic compounds (NMVOC) warm by increasing both O(3) and CH(4). Radiative impacts from secondary organic aerosols (SOA) are poorly understood. Black carbon emission controls, by reducing the absorption of sunlight in the atmosphere and on snow and ice, have the potential to slow near-term warming, but uncertainties in coincident emissions of reflective (cooling) aerosols and poorly constrained cloud indirect effects confound robust estimates of net climate impacts. Reducing sulfate and nitrate aerosols would improve air quality and lessen interference with the hydrologic cycle, but lead to warming. A holistic and balanced view is thus needed to assess how air pollution controls influence climate; a first step towards this goal involves estimating net climate impacts from individual emission sectors. Modeling and observational analyses suggest a warming climate degrades air quality (increasing surface O(3) and particulate matter) in many populated regions, including during pollution episodes. Prior Intergovernmental Panel on Climate Change (IPCC) scenarios (SRES) allowed unconstrained growth, whereas the Representative Concentration Pathway (RCP) scenarios assume uniformly an aggressive reduction, of air pollutant emissions. New estimates from the current generation of chemistry-climate models with RCP emissions thus project improved air quality over the next century relative to those using the IPCC SRES scenarios. These two sets of projections likely bracket possible futures. We find that uncertainty in emission-driven changes in air quality is generally greater than uncertainty in climate-driven changes. Confidence in air quality projections is limited by the reliability of anthropogenic emission trajectories and the uncertainties in regional climate responses, feedbacks with the terrestrial biosphere, and oxidation pathways affecting O(3) and SOA.
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Affiliation(s)
- Arlene M Fiore
- Department of Earth and Environmental Sciences and Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA.
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Barlage M, Chen F, Tewari M, Ikeda K, Gochis D, Dudhia J, Rasmussen R, Livneh B, Ek M, Mitchell K. Noah land surface model modifications to improve snowpack prediction in the Colorado Rocky Mountains. ACTA ACUST UNITED AC 2010. [DOI: 10.1029/2009jd013470] [Citation(s) in RCA: 110] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Parrish DD, Allen DT, Bates TS, Estes M, Fehsenfeld FC, Feingold G, Ferrare R, Hardesty RM, Meagher JF, Nielsen-Gammon JW, Pierce RB, Ryerson TB, Seinfeld JH, Williams EJ. Overview of the Second Texas Air Quality Study (TexAQS II) and the Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS). ACTA ACUST UNITED AC 2009. [DOI: 10.1029/2009jd011842] [Citation(s) in RCA: 139] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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