Poisson, negative binomial, and zero-inflated negative binomial regression models for predicting daily airborne pollen concentration levels in Sinop (Türkiye)
 
Yazarlar (7)
Ayten Yiğiter Hacettepe Üniversitesi, Türkiye
Cemile Canşı Demir Science High School, Türkiye
Canan Hamurkaroğlu Karabük Üniversitesi, Türkiye
Prof. Dr. Hülya ÖZLER Sinop Üniversitesi, Türkiye
Doç. Dr. Ayşe Kaplan Zonguldak Bulent Ecevit University, Türkiye
Dr. Öğr. Üyesi Nazan DANACIOĞLU Sinop Üniversitesi, Türkiye
Sümeyra Sezer Kaplan Karabük Üniversitesi, Türkiye
Makale Türü Açık Erişim Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
Dergi Adı Environmental Monitoring and Assessment (Q3)
Dergi ISSN 0167-6369 Dergi Bilgileri (2026)
Dergi Tarandığı Indeksler SCI-Expanded
Makale Dili İngilizce Basım Tarihi 01-2026
Kabul Tarihi 29-11-2025 Yayınlanma Tarihi 12-12-2025
Cilt / Sayı / Sayfa 198 / 1 / 1–14 DOI 10.1007/s10661-025-14871-0
Makale Linki https://pubmed.ncbi.nlm.nih.gov/41385146/
UAK Araştırma Alanları
Uygulamalı İstatistik İstatistiksel Analiz Teorik İstatistik
Özet
Pollen, produced during the flowering period of plants, especially anemogamous plants that produce high volumes of pollen, poses a risk to individuals with pollen allergies when it is present in the atmosphere. Meteorological factors are known to affect the duration, distribution, and amount of pollen in the air. The remarkable increase in allergic cases in recent years has led to many studies investigating the relationship between pollen and spores that cause allergies and meteorological factors in Türkiye as well as in the world. In this study, meteorological factors and their influence on pollen concentrations in the air were examined for the Sinop region in northern Türkiye. First, descriptive statistics for pollen obtained from plant taxa were obtained and interpreted. Precipitation, humidity, temperature, and wind speed were considered as meteorological parameters, and the effects of these variables on pollen counts …
Anahtar Kelimeler
Negative binomial regression; | Zero-inflated negative binomial regression | Pollen | Poisson regression;