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Shipping in the north-east Atlantic: Identifying spatial and temporal patterns of change

MARINE POLLUTION BULLETIN 2022年 179卷 113681页

作者： Robbins, James R. Bouchet, Phil J. Miller, David L. Evans, Peter G. H. Waggitt, James Ford, Alex T. Marley, Sarah A. Univ Portsmouth Inst Marine Sci Ferry RdEastney Portsmouth PO4 9LY England Univ St Andrews Sch Math & Stat Observatory St Andrews KY16 9LZ Scotland Bangor Univ Sch Ocean Sci Menai BridgeAnglesey Bangor LL59 5AB Wales Sea Watch Fdn Ewyn y DonBull BayAmlwch Anglesey LL68 9SD Wales Scotlands Rural Coll SRUC Craibstone Estate Aberdeen AB21 9YA Scotland Univ St Andrews Ctr Res Ecol & Environm Modelling Observatory St Andrews KY16 9LZ Scotland

Maritime traffic is increasing globally, with a four-fold increase in commercial vessel movements between 1992 and 2012. Vessels contribute to noise and air pollution, provide pathways for non-native species, and collide with marine wildlife. While knowledge of shipping trends and potential environmental impacts exists at both local and global levels, key information on vessel density for regional-scale management is lacking. This study presents the first in-depth spatio-temporal analysis of shipping in the north-east Atlantic region, over three years in a five-year period. Densities increased by 34%, including in 73% of Marine Protected Areas. Western Scotland and the Bay of Biscay experienced the largest increases in vessel density, predominantly from small and slow vessels. Given well-documented impacts that shipping can have on the marine environment, it is crucial that this situation continues to be monitored - particularly in areas designated to protect vulnerable species and ecosystems which may already be under pressure.

关键词： Marine conservation Marine protected area Maritime traffic Automatic identification system Vessel density generalized additive model

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Temperature, humidity and outdoor air quality indicators influence COVID-19 spread rate and mortality in major cities of Saudi Arabia

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ENVIRONMENTAL RESEARCH 2022年第PartB期204卷 112071-112071页

作者： Ismail, Iqbal M. I. Rashid, Muhammad Imtiaz Ali, Nadeem Altaf, Bothinah Abdullah Saeed Munir, Muhammad King Abdulaziz Univ Ctr Excellence Environm Studies POB 80216 Jeddah 21589 Saudi Arabia King Abdulaziz Univ Dept Chem Fac Sci POB 80203 Jeddah 21589 Saudi Arabia King Abdulaziz Univ Dept Stat Fac Sci Female CampusPOB 80203 Jeddah 21589 Saudi Arabia Univ Lancaster Div Biomed & Life Sci Lancaster England

There is an increasing evidence that meteorological (temperature, relative humidity, dew) and air quality in-dicators (PM2.5, PM10, NO2, SO2, CO) are affecting the COVID-19 transmission rate and the number of deaths in many countries around the globe. However, there are contradictory results due to limited observations of these parameters and absence of conclusive evidence on such relationships in cold or hot arid tropical and subtropical desert climate of Gulf region. This is the first study exploring the relationships of the meteorological (temper-ature, relative humidity, and dew) and air quality indicators (PM10,CO, and SO2) with daily COVID-19 infections and death cases for a period of six months (1st March to August 31, 2020) in six selected cities of the Kingdom of Saudi Arabia by using generalized additive model. The Akaike information criterion (AIC) was used to assess factors affecting the infections rate and deaths through the selection of best model whereas overfitting of multivariate model was avoided by using cross-validation. Spearman correlation indicated that exponentially weighted moving average (EWMA) temperature and relative humidity (R 0.0001) are the main variables affecting the daily COVID-19 infections and deaths. EWMA temperature and relative humidity showed non linear relationships with the number of COVID-19 infections and deaths (DF1, P < 0.0001). Daily COVID-19 infections showed a positive relationship at temperature between 23 and 34.5 degrees C and relative humidity ranging from 30 to 60%;a negative relationship was found below and/or above these ranges. Similarly, the number of deaths had a positive relationship at temperature >28.7 degrees C and with relative humidity <40%, showing higher number of deaths above this temperature and below this relative humidity rate. All air quality indicators had linear relationships with the number of COVID-19 infections and deaths (P < 0.0001). Hence, variation in temperature, relative humidity and

关键词： Air pollution Arid tropical and subtropical desert climate COVID-19 generalized additive model Gulf

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Correcting citizen-science air temperature measurements across the Netherlands for short wave radiation bias

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METEOROLOGICAL APPLICATIONS 2020年第1期27卷 e1814-e1814页

作者： Cornes, Richard C. Dirksen, Marieke Sluiter, Raymond Royal Netherlands Meteorol Inst KNMI R&D Observat & Data Technol De Bilt Netherlands Natl Oceanog Ctr Southampton Hants England

Citizen-science thermometer measurements have the potential to provide information about surface air temperature fields on scales smaller than is typically quantified by the official monitoring network. As such, national meteorological services are becoming increasingly interested in these measurements as a possible source of data for use in weather monitoring or forecasting. However, in order for the information to be used, biases in the data need to be assessed. The most important source of bias is the potential overheating of the thermometer due to inadequate shielding or exposure. Previous research has indicated that information about the nature of the instrument and its exposure is important for correcting this bias. However, in the majority of cases this information is unavailable for amateur stations. In this paper a statistical correction for short wave radiation bias is developed for the air temperature data recorded at 159 Weather Observations Website (WOW) stations across the Netherlands during the period 2015-2016. generalized additive mixed modelling (GAMM) is used to quantify and correct for short wave radiation bias in the hourly measurements using a background temperature field generated from the official 34 automatic weather stations along with satellite-derived short wave radiation estimates. It is demonstrated that the corrected WOW data add local detail to the hourly temperature field, which may provide a useful source of data to supplement official measurements.

关键词： amateur observations crowd sourced generalized additive model private weather stations urban heat island

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Effect of air pollution on hospitalization for acute exacerbation of chronic obstructive pulmonary disease, stroke, and myocardial infarction

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2020年第3期27卷 3384-3400页

作者： Chen, Cai Liu, Xuejian Wang, Xianfeng Qu, Wenxiu Li, Wei Dong, Leilei Shandong Univ Sch Control Sci & Engn Biomed Engn Inst Jinan 250061 Peoples R China China Med Univ Shengjing Hosp Gen Internal Med 1 16 Puhe Rd Shenyang 110000 Liaoning Peoples R China Shandong Univ PFLMET Expt Ctr Jinan Peoples R China

This study aims to analyze the acute effects of PM2.5, PM10, SO2, NO2, and O-3 on hospitalizations for acute exacerbation of chronic obstructive pulmonary disease (AECOPD), stroke, and myocardial infarction (MI) from 2014 to 2017 in Shenyang, China. Hospitalization records for AECOPD (17,655), stroke (276,736) and MI (26,235) and air pollutions concentration data (PM2.5, PM10, SO2, NO2, and O-3) were collected. A generalized additive model (GAM) was utilized to determine the impact of air pollutants on the relative risk (RR) of hospitalization for AECOPD, stroke, and MI. Stratified analysis for AECOPD was based on gender and age. It was based on gender, age, hypertension, and diabetes for stroke, and for MI it was based on gender, age, and coronary atherosclerosis. The lag effect for AECOPD in terms of gender analysis occurred at lag3-lag5. The hospitalization risk for stroke with hypertension due to SO2 and NO2 was greater than that of stroke without hypertension. The risk of hospitalization for stroke with hypertension as a comorbidity due to O-3 was lower than without hypertension. The risk of hospitalization for MI combined with coronary atherosclerosis due to PM2.5, PM10, or NO2 was higher than that of hospitalizations for MI without coronary atherosclerosis. Air pollution increased the rate of hospitalization for AECOPD. SO2 and O-3 appeared protective for stroke patients with coronary atherosclerosis. PM2.5, PM10, and NO2 had no influence on total hospitalization for myocardial infarction.

关键词： Air pollution Hospitalization generalized additive model Acute exacerbation of chronic obstructive pulmonary disease Stroke Myocardial infarction Hypertension Coronary atherosclerosis

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Urinary paraben exposure increases the risk of a low estimated glomerular filtration rate in Taiwanese general population

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Ecotoxicology and Environmental Safety 2024年 283卷 116775页

作者： Huang, Po-Chin Huang, Yen-Hsuan Chen, Hsin-Chang Lin, Yu-Jung Chang, Wan-Ting Chang, Jung-Wei National Institute of Environmental Health Sciences National Health Research Institutes Department of Medical Research China Medical University Hospital China Medical University Research Center for Precision Environmental Medicine Kaohsiung Medical University Institute of Environmental and Occupational Health Sciences School of Medicine National Yang Ming Chiao Tung University Department of Chemistry College of Science Tunghai University

Background: The inconsistent relationship between chemical exposure and estimated glomerular filtration rate (eGFR) has been examined in only a few studies. We investigated the association between paraben exposure and indicators of renal function in a total of 361 individuals recruiting from a representative study. Method: The levels of urinary parabens, including methylparaben (MeP), ethylparaben (EtP), propylparaben (PrP), and butylparaben (BuP), were measured using UPLC-MS/MS. The association between paraben exposure and indices of renal function was assessed using multiple logistic regression and Bayesian Kernel Machine Regression (BKMR). Results: The median levels of urinary parabens in the adult group were significantly higher than those in the minor group, that is, 397 vs. 148 ng/mL for MeP, 38.8 vs. 13.6 ng/mL for EtP, 117 vs. 57.7 ng/mL for PrP, and 6.61 vs. 2.79 ng/mL for BuP (all P < 0.001). In the adult group, multivariate regression models confirmed a positive association between the albumin-to-creatinine ratio and urinary MeP (β = 0.580) and a positive association of BUN (β = 0.061) and a negative association of eGFR (β = −0.051) with urinary EtP (all P < 0.001). In the adult group, compared with the lowest tertile group, the adjusted odds ratio in the third tertile (T₃) of urinary EtP levels indicated a 3.08 times increased risk of eGFR abnormalities, followed by the second tertile (T₂) with a 2.63 times increased risk. The generalized additive model (GAM) and BKMR models showed a non-linear correlation between urinary EtP levels and early CKD, as well as reduced eGFR. We observed a significant positive cumulative effect of urinary paraben on eGFR, and a significant positive single exposure effect of urinary EtP with eGFR abnormality. Conclusion: We found a significant association between exposure to EtP and an increased risk of high BUN levels and decreased eGFR. © 2024

关键词： Albumin-to-creatinine ratio Estimated glomerular filtration rate (eGFR) generalized additive model Parabens

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A Comparison of models of Stand Volume in Spruce-Fir Mixed Forest in Northeast China

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FORESTS 2022年第7期13卷 1117页

作者： Liu, Jiarong He, Jingyuan Chai, Lei Zhong, Xun Jia, Bo Wang, Xinjie Beijing Forestry Univ Coll Forestry Beijing 100091 Peoples R China

Based on a multiple linear regression model, random forest algorithm and generalized additive model, a stand volume model was constructed to provide a theoretical basis for sustainable management. A total of 224 fixed plots in the Jingouling forest farm, Wangqing County, Jilin Province, were used as data sources. Specifically, 157 plots were used as training data, and 77 plots were used as test data. The effects of stand structure variables, topography variables, cutting variables, diversity variables and climate variables on stand volume were analyzed. The random forest algorithm explained 95.51% of the stand volume, and the generalized additive model explained 95.45% of the stand volume. Stand structure variables and topography variables had more influence on the stand volume of spruce-fir than other variables. Among the diversity variables, the evenness index, Shannon index and Simpson index had a relatively greater impact on the stand volume. The cutting times and the intensity of the first cutting had a direct relationship with stand volume. The influence of climate variables on the stand volume was relatively small in the study area.

关键词： linear regression model random forest generalized additive model spruce-fir stand volume

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Lag Effect of Temperature and Humidity on COVID-19 Cases in 11 Chinese Cities

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ATMOSPHERE 2022年第9期13卷 1486-1486页

作者： Feng, Fengliu Ma, Yuxia Cheng, Bowen Zhang, Yifan Li, Heping Qin, Pengpeng Lanzhou Univ Coll Atmospher Sci Key Lab Semiarid Climate Change Minist Educ Lanzhou 730000 Peoples R China

The global transmission of COVID-19 has caused considerable health burdens, and epidemiological studies have proven that temperature and humidity play an important role in the transmission of infectious respiratory diseases. This effect may not be immediate and can be delayed by days to weeks. In this study, the comprehensive effect of temperature and humidity on COVID-19 was evaluated using the discomfort index (DI). We analyzed the lag effect of the DI on COVID-19 from 21 January to 29 February 2020 in 11 Chinese cities by designing a generalized additive model (GAM). We classified the 11 Chinese cities into southern cities and northern cities to compare the potential effects in these two types of cities. The results reveal that the DI had the same negative correlation and different lag effects on daily COVID-19 cases. There was a significant negative correlation between the DI and daily COVID-19 cases (p < 0.05), except in Wuhan. The lag effect was stronger in the cities located further north. In northern cities, each unit decrease in the DI increased the COVID-19 risk from 7 to 13 lag days. In southern China, each unit decrease in the DI increased the COVID-19 risk from 0 to 7 lag days, especially in Shanghai, Guangzhou, and Shenzhen.

关键词： generalized additive model COVID-19 lag effect discomfort index

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Analysis of the Effect of Economic Development on Air Quality in Jiangsu Province Using Satellite Remote Sensing and Statistical modeling

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ATMOSPHERE 2022年第5期13卷 697-697页

作者： Jia, Jia You, Yan Yang, Shanlin Shang, Qingmei Hefei Univ Technol Sch Management Hefei 230009 Peoples R China Hefei Univ Sch Econ & Management Hefei 230601 Peoples R China Macau Univ Sci & Technol Macao Environm Res Inst Natl Observat & Res Stn Coastal Ecol Environm Mac Macau 999078 Peoples R China

In recent decades, the economy of China has developed rapidly, but this has brought widespread damage to the environment, which forces us to explore a sustainable, green, economic development model. Therefore, it is particularly necessary to clarify the relationship between economic development and environmental pollution. In this paper, we used satellite remote sensing tropospheric NO2 vertical column density (VCD) as an air quality indicator;the total exports, total imports, and industrial electricity consumption as the economic indicators;and the wind speed, temperature, and planetary boundary layer height as the meteorological factors to perform a generalized additive modeling (GAM) analysis. By deducing the influence of meteorological factors, the relationship between economic indicators and the air quality indicator can be determined. When total exports increased by one billion USD (United States Dollar), the tropospheric NO2 VCDs of Nanjing and Suzhou increased by about 15% and 6%, respectively. The tropospheric NO2 VCDs of Suzhou increased by about 5% when the total imports increased by one billion USD. In addition, when the industrial electricity consumption increased by one billion kWh, the tropospheric NO2 VCDs of Nanjing, Suzhou and Xuzhou increased by about 25%, 12%, and 59%, respectively. This study provides a method to quantify the contribution of economic growth to air pollution, which is helpful for better understanding of the relationship between economic development and air quality.

关键词： satellite remote sensing nitrogen dioxide air quality economic indicators generalized additive model

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Investigating the Relationship Between Air Quality and COVID-19 Transmission

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Journal of Data Science 2021年第3期19卷 485-497页

作者： Albrecht, Laura Czarnecki, Paulina Sakelaris, Bennet Department of Applied Mathematics and Statistics Colorado School of Mines Golden CO United States Department of Applied Physics and Applied Mathematics Columbia University New York City NY United States Department of Engineering Sciences and Applied Mathematics Northwestern University Evanston IL United States

It is hypothesized that short-term exposure to air pollution may influence the transmission of aerosolized pathogens such as COVID-19. We used data from 23 provinces in Italy to build a generalized additive model to investigate the association between the effective reproductive number of the disease and air quality while controlling for ambient environmental variables and changes in human mobility. The model finds that there is a positive, nonlinear relationship between the density of particulate matter in the air and COVID-19 transmission, which is in alignment with similar studies on other respiratory illnesses. © 2021 Center for Applied Statistics, School of Statistics, Renmin University of China. All rights reserved.

关键词： air pollution effective reproduction number generalized additive model mobility particulate matter

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The Impact of Environmental and Host Factors on Human Cystic Echinococcosis: A County-Level modeling Study in Western China

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GEOHEALTH 2023年第6期7卷 e2022GH000721页

作者： Yin, Jie Wu, Xiaoxu Li, Chenlu Han, Jiatong Xiang, Hongxu Beijing Normal Univ Fac Geog Sci State Key Lab Remote Sensing Sci Beijing Peoples R China

Human cystic echinococcosis (CE) is a parasitic disease caused by tapeworms from the Echinococcus granulosus genus, potentially affected by the environment and host animals. West China is one of the most endemic areas of human CE nation and worldwide. The current study identifies the crucial environmental and host factors of human CE prevalence in the Qinghai-Tibet Plateau and non-Qinghai-Tibet Plateau regions. An optimal county-level model was used to analyze the association between key factors and human CE prevalence within the Qinghai-Tibet Plateau. Geodetector analysis and multicollinearity tests identify key factors, and an optimal model is developed through generalized additive models. In the Qinghai-Tibet Plateau, four key factors were identified from the 88 variables, such as maximum annual precipitation (Pre), maximum summer normalized difference vegetation index (NDVI), Tibetan population rate (TibetanR), and positive rates of Echinococcus coproantigen in dogs (DogR). Based on the optimal model, a significant positive linear relationship was observed between maximum annual Pre and human CE prevalence. A probable U-shaped curve depicts the non-linear relationship between maximum summer NDVI and the human CE prevalence. Human CE prevalence possesses significant positive non-linear relationships with TibetanR and DogR. Human CE transmission is integrally affected by environmental and host factors. This explains the mechanism of human CE transmission based on the pathogen, host, and transmission framework. Therefore, the current study provides references and innovative ideas for preventing and controlling human CE in western *** Language Summary Western China is one of the most prevalent epidemic areas of human cystic echinococcosis (CE) worldwide. This region is closely associated with the natural environment, human society, and host animals. The relative contribution of the natural and human environments and host factors to human CE prevalence has be

关键词： cystic echinococcosis Qinghai-Tibet Plateau county level environment impact host generalized additive model

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