Pub Date : 2024-02-22DOI: 10.1007/s10666-024-09961-1
D. Mirakovski, A. Zendelska, B. Boev, M. Hadži-Nikolova, Tena Shijakova-Ivanova, Nikolinka Doneva, I. Boev, Gorgi Dimov, Elena Doneva, Ana Mihailovska
{"title":"Evaluation of PM2.5 Sources in Skopje Urban Area Using Positive Matrix Factorization","authors":"D. Mirakovski, A. Zendelska, B. Boev, M. Hadži-Nikolova, Tena Shijakova-Ivanova, Nikolinka Doneva, I. Boev, Gorgi Dimov, Elena Doneva, Ana Mihailovska","doi":"10.1007/s10666-024-09961-1","DOIUrl":"https://doi.org/10.1007/s10666-024-09961-1","url":null,"abstract":"","PeriodicalId":50515,"journal":{"name":"Environmental Modeling & Assessment","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139957530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-16DOI: 10.1007/s10666-024-09955-z
Monia Landolsi, K. Miled
{"title":"Reducing GHG Emissions by Improving Energy Efficiency: A Decomposition Approach","authors":"Monia Landolsi, K. Miled","doi":"10.1007/s10666-024-09955-z","DOIUrl":"https://doi.org/10.1007/s10666-024-09955-z","url":null,"abstract":"","PeriodicalId":50515,"journal":{"name":"Environmental Modeling & Assessment","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139833513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-16DOI: 10.1007/s10666-024-09955-z
Monia Landolsi, K. Miled
{"title":"Reducing GHG Emissions by Improving Energy Efficiency: A Decomposition Approach","authors":"Monia Landolsi, K. Miled","doi":"10.1007/s10666-024-09955-z","DOIUrl":"https://doi.org/10.1007/s10666-024-09955-z","url":null,"abstract":"","PeriodicalId":50515,"journal":{"name":"Environmental Modeling & Assessment","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139773984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.1007/s10666-024-09954-0
Le Thanh Ha
{"title":"Dynamic Interrelations Between Environmental Innovations, Human Capital, and Energy Security in Vietnam: New Evidence from an Extended QVAR Approach","authors":"Le Thanh Ha","doi":"10.1007/s10666-024-09954-0","DOIUrl":"https://doi.org/10.1007/s10666-024-09954-0","url":null,"abstract":"","PeriodicalId":50515,"journal":{"name":"Environmental Modeling & Assessment","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139783920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.1007/s10666-024-09954-0
Le Thanh Ha
{"title":"Dynamic Interrelations Between Environmental Innovations, Human Capital, and Energy Security in Vietnam: New Evidence from an Extended QVAR Approach","authors":"Le Thanh Ha","doi":"10.1007/s10666-024-09954-0","DOIUrl":"https://doi.org/10.1007/s10666-024-09954-0","url":null,"abstract":"","PeriodicalId":50515,"journal":{"name":"Environmental Modeling & Assessment","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139843679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-20DOI: 10.1007/s10666-024-09953-1
Ronald Djeunankan, Henri Njangang, Honoré Tékam Oumbé
{"title":"Examining the Effect of Economic Complexity on Energy Poverty in Developing Countries","authors":"Ronald Djeunankan, Henri Njangang, Honoré Tékam Oumbé","doi":"10.1007/s10666-024-09953-1","DOIUrl":"https://doi.org/10.1007/s10666-024-09953-1","url":null,"abstract":"","PeriodicalId":50515,"journal":{"name":"Environmental Modeling & Assessment","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139523986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-19DOI: 10.1007/s10666-024-09952-2
S. Erdoğan, U. Pata, M. Kartal
{"title":"Exploring the Cost of Decarbonizing the United States: A Proposal for a Green Sacrifice Ratio","authors":"S. Erdoğan, U. Pata, M. Kartal","doi":"10.1007/s10666-024-09952-2","DOIUrl":"https://doi.org/10.1007/s10666-024-09952-2","url":null,"abstract":"","PeriodicalId":50515,"journal":{"name":"Environmental Modeling & Assessment","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139525721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-13DOI: 10.1007/s10666-023-09951-9
Benjamin Ouvrard, Anne Stenger
{"title":"Informational Nudges and Environmental Preferences in a Public Goods Game in Networks","authors":"Benjamin Ouvrard, Anne Stenger","doi":"10.1007/s10666-023-09951-9","DOIUrl":"https://doi.org/10.1007/s10666-023-09951-9","url":null,"abstract":"","PeriodicalId":50515,"journal":{"name":"Environmental Modeling & Assessment","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139437562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-11DOI: 10.1007/s10666-023-09950-w
Caitlin Cunningham, K. Beazley, Peter G. Bush, J. Brazner
{"title":"Addressing the Boundary and Modifiable Areal Unit Problems Simultaneously when Measuring Landscape Fragmentation Using Patch-Based Metrics: a Case Study of Effective Mesh Size in Nova Scotia, Canada","authors":"Caitlin Cunningham, K. Beazley, Peter G. Bush, J. Brazner","doi":"10.1007/s10666-023-09950-w","DOIUrl":"https://doi.org/10.1007/s10666-023-09950-w","url":null,"abstract":"","PeriodicalId":50515,"journal":{"name":"Environmental Modeling & Assessment","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139438461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-14DOI: 10.1007/s10666-023-09943-9
Amirhossein Hassani, Gabriela Sousa Santos, Philipp Schneider, Núria Castell
Abstract Fine-resolution spatio-temporal maps of near-surface urban air temperature ( T a ) provide crucial data inputs for sustainable urban decision-making, personal heat exposure, and climate-relevant epidemiological studies. The recent availability of IoT weather station data allows for high-resolution urban T a mapping using approaches such as interpolation techniques or machine learning (ML). This study is aimed at executing these approaches and traditional numerical modeling within a practical and operational framework and evaluate their practicality and efficiency in cases where data availability, computational constraints, or specialized expertise pose challenges. We employ Netatmo crowd-sourced weather station data and three geospatial mapping approaches: (1) Ordinary Kriging, (2) statistical ML model (using predictors primarily derived from Earth Observation Data), and (3) weather research and forecasting model (WRF) to predict/map daily T a at nearly 1-km spatial resolution in Warsaw (Poland) for June–September and compare the predictions against observations from 5 meteorological reference stations. The results reveal that ML can serve as a viable alternative approach to traditional kriging and numerical simulation, characterized by reduced complexity and higher computational speeds within the domain of urban meteorological studies (overall RMSE = 1.06 °C and R 2 = 0.94, compared to ground-based meteorological stations). The results have implications for identifying the urban regions vulnerable to overheating and evidence-based urban management in response to climate change. Due to the open-sourced nature of the applied predictors and input parsimony, the ML method can be easily replicated for other EU cities.
{"title":"Interpolation, Satellite-Based Machine Learning, or Meteorological Simulation? A Comparison Analysis for Spatio-temporal Mapping of Mesoscale Urban Air Temperature","authors":"Amirhossein Hassani, Gabriela Sousa Santos, Philipp Schneider, Núria Castell","doi":"10.1007/s10666-023-09943-9","DOIUrl":"https://doi.org/10.1007/s10666-023-09943-9","url":null,"abstract":"Abstract Fine-resolution spatio-temporal maps of near-surface urban air temperature ( T a ) provide crucial data inputs for sustainable urban decision-making, personal heat exposure, and climate-relevant epidemiological studies. The recent availability of IoT weather station data allows for high-resolution urban T a mapping using approaches such as interpolation techniques or machine learning (ML). This study is aimed at executing these approaches and traditional numerical modeling within a practical and operational framework and evaluate their practicality and efficiency in cases where data availability, computational constraints, or specialized expertise pose challenges. We employ Netatmo crowd-sourced weather station data and three geospatial mapping approaches: (1) Ordinary Kriging, (2) statistical ML model (using predictors primarily derived from Earth Observation Data), and (3) weather research and forecasting model (WRF) to predict/map daily T a at nearly 1-km spatial resolution in Warsaw (Poland) for June–September and compare the predictions against observations from 5 meteorological reference stations. The results reveal that ML can serve as a viable alternative approach to traditional kriging and numerical simulation, characterized by reduced complexity and higher computational speeds within the domain of urban meteorological studies (overall RMSE = 1.06 °C and R 2 = 0.94, compared to ground-based meteorological stations). The results have implications for identifying the urban regions vulnerable to overheating and evidence-based urban management in response to climate change. Due to the open-sourced nature of the applied predictors and input parsimony, the ML method can be easily replicated for other EU cities.","PeriodicalId":50515,"journal":{"name":"Environmental Modeling & Assessment","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134991857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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