Spatiotemporal of Particulate Matter (PM2.5) and Ozone (O3) in Eastern Northeast Brazil

被引:0
作者
de Souza, Amaury [1 ]
Ozonur, Deniz [2 ]
de Medeiros, Elias Silva [3 ]
Pobocikova, Ivana [4 ]
de Oliveira-Junior, Jose Francisco [5 ]
Jimenez, Jose Roberto Zenteno [6 ]
Cardoso, Kelvy Rosalvo Alencar [5 ]
Abreu, Marcel Carvalho [7 ]
Pansera, Wagner Alessandro [8 ]
Cavazzana, Guilherme Henrique [1 ]
机构
[1] Univ Fed Mato Grosso do Sul, Phys Inst, BR-79070900 Campo Grande, MS, Brazil
[2] Gazi Univ, Fac Sci, Dept Stat, TR-06560 Ankara, Turkiye
[3] Fed Univ Grande Dourados, Fac Exact Sci & Technol, BR-79825070 Dourados, MS, Brazil
[4] Univ Zilina, Fac Mech Engn, Dept Appl Math, Zilina 01026, Slovakia
[5] Univ Fed Alagoas, Inst Atmospher Sci ICAT, BR-57072900 Maceio, Brazil
[6] Ingn Geofis Inst Politecn Nacl Ciudad Mexico ESIA, Dept Ingn Petrolera, Ticoman 07340, Mexico
[7] Rural Fed Univ Rio De Janeiro, Phys Inst, BR-23890000 Seropedica, RJ, Brazil
[8] Fed Univ Technol Parana UTFPR, Dept Civil Engn, BR-85902490 Toledo, PR, Brazil
关键词
Modeling; ozone; particulate matter; pollution; urban area; AIR-POLLUTANTS; TEMPORAL VARIABILITY; PM LEVELS; URBAN; INDUSTRIAL; SITES; PATTERNS; CITIES; AREA; NO2;
D O I
10.1080/01919512.2024.2388597
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This research examines particulate matter with a diameter of 2.5 micrometers (PM2.5) and ozone (O-3) variation across the climatic mesoregions of Alagoas. Mean PM2.5 and O-3 concentrations across three mesoregions were as follows: East (5.91; 44.22 mu g.m(-3)), Hinterland (6.90; 44.18 mu g.m(-3)), and Arid (7.03; 44.23 mu g.m(-3)). Spatial and temporal variations were observed, with PM2.5 concentrations highest in the northwest (NW) and O-3 concentrations in the east (E), influenced by local sources, weather, and transportation. Differences between rainy and dry years were noted, attributed to biomass burning and dust particle transport. This study establishes a baseline for understanding air quality, lacking monitoring stations, aiding policymaking. It provides insights into PM2.5 and O-3 dynamics, with PM2.5 concentrations highest in the NW and lower O-3 concentrations in the E. Temporal variations emphasize the need for dynamic monitoring. Positive correlations between PM2.5 and O-3 highlight complex relationships. Practical implications include proactive policymaking and the necessity for monitoring stations. Rigorous statistical methodologies inform model selection, enhancing environmental data understanding. Despite changes in land use, studies on extreme probability distributions are limited, emphasizing the need for robust methodologies for environmental data analysis to address air pollution challenges effectively in Alagoas.
引用
收藏
页码:91 / 104
页数:14
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