Individuals,local communities,environmental associations,private organizations,and public representatives and bodies may all be aggrieved by environmental problems concerning poor air quality,illegal waste disposal,wa...Individuals,local communities,environmental associations,private organizations,and public representatives and bodies may all be aggrieved by environmental problems concerning poor air quality,illegal waste disposal,water contamination,and general pollution.Environmental complaints represent the expressions of dissatisfaction with these issues.As the timeconsuming of managing a large number of complaints,text mining may be useful for automatically extracting information on stakeholder priorities and concerns.The paper used text mining and semantic network analysis to crawl relevant keywords about environmental complaints from two online complaint submission systems:online claim submission system of Regional Agency for Prevention,Environment and Energy(Arpae)(“Contact Arpae”);and Arpae's internal platform for environmental pollution(“Environmental incident reporting portal”)in the Emilia-Romagna Region,Italy.We evaluated the total of 2477 records and classified this information based on the claim topic(air pollution,water pollution,noise pollution,waste,odor,soil,weather-climate,sea-coast,and electromagnetic radiation)and geographical distribution.Then,this paper used natural language processing to extract keywords from the dataset,and classified keywords ranking higher in Term Frequency-Inverse Document Frequency(TF-IDF)based on the driver,pressure,state,impact,and response(DPSIR)framework.This study provided a systemic approach to understanding the interaction between people and environment in different geographical contexts and builds sustainable and healthy communities.The results showed that most complaints are from the public and associated with air pollution and odor.Factories(particularly foundries and ceramic industries)and farms are identified as the drivers of environmental issues.Citizen believed that environmental issues mainly affect human well-being.Moreover,the keywords of“odor”,“report”,“request”,“presence”,“municipality”,and“hours”were the most influential and meaningful concepts,as demonstrated by their high degree and betweenness centrality values.Keywords connecting odor(classified as impacts)and air pollution(classified as state)were the most important(such as“odor-burnt plastic”and“odor-acrid”).Complainants perceived odor annoyance as a primary environmental concern,possibly related to two main drivers:“odor-factory”and“odorsfarms”.The proposed approach has several theoretical and practical implications:text mining may quickly and efficiently address citizen needs,providing the basis toward automating(even partially)the complaint process;and the DPSIR framework might support the planning and organization of information and the identification of stakeholder concerns and priorities,as well as metrics and indicators for their assessment.Therefore,integration of the DPSIR framework with the text mining of environmental complaints might generate a comprehensive environmental knowledge base as a prerequisite for a wider exploitation of analysis to support decision-making processes and environmental management activities.展开更多
Rapid urbanization has markedly affected urban ecosystem health(EH),making it imperative to explore the relationships between EH and urbanization,as well as to identify the key factors influencing EH.This study addres...Rapid urbanization has markedly affected urban ecosystem health(EH),making it imperative to explore the relationships between EH and urbanization,as well as to identify the key factors influencing EH.This study addresses 2 key research gaps:(a)The traditional pressure–state–response evaluation framework fails to integrate ecosystem service demands and landscape pattern indices and has not formed a comprehensive EH evaluation system.(b)There is a lack of research on investigating the drivers and thresholds of EH across the areas in different spatial relationship between urbanization and EH at the urban scale.Here,taking Wuhan,China,as an example,this study assesses EH utilizing an optimized pressure–state–response evaluation framework.Additionally,bivariate Moran’s I is used to analyze the spatial relationship between EH and urbanization.We use gradient boosting decision trees to flexibly model the nonlinear relationships between influencing factors and EH,while Shapley additive explanations quantify each factor’s contribution,enhancing model interpretability and clarifying their effects on EH.The findings reveal a spatial distribution pattern characterized by lower EH levels in central areas and higher EH levels in periphery areas,with a notable negative spatial correlation between EH and urbanization.The spatial heterogeneity and clustering of EH and urbanization across Wuhan exhibit a ringlike pattern radiating from the center to the periphery.Landscape pattern index and land use are identified as key influencing factors of EH in Wuhan,with substantial regional variation,necessitating targeted environmental protection strategies.This study offers insights into urban planning and policymaking,promoting sustainable urban development.展开更多
文摘Individuals,local communities,environmental associations,private organizations,and public representatives and bodies may all be aggrieved by environmental problems concerning poor air quality,illegal waste disposal,water contamination,and general pollution.Environmental complaints represent the expressions of dissatisfaction with these issues.As the timeconsuming of managing a large number of complaints,text mining may be useful for automatically extracting information on stakeholder priorities and concerns.The paper used text mining and semantic network analysis to crawl relevant keywords about environmental complaints from two online complaint submission systems:online claim submission system of Regional Agency for Prevention,Environment and Energy(Arpae)(“Contact Arpae”);and Arpae's internal platform for environmental pollution(“Environmental incident reporting portal”)in the Emilia-Romagna Region,Italy.We evaluated the total of 2477 records and classified this information based on the claim topic(air pollution,water pollution,noise pollution,waste,odor,soil,weather-climate,sea-coast,and electromagnetic radiation)and geographical distribution.Then,this paper used natural language processing to extract keywords from the dataset,and classified keywords ranking higher in Term Frequency-Inverse Document Frequency(TF-IDF)based on the driver,pressure,state,impact,and response(DPSIR)framework.This study provided a systemic approach to understanding the interaction between people and environment in different geographical contexts and builds sustainable and healthy communities.The results showed that most complaints are from the public and associated with air pollution and odor.Factories(particularly foundries and ceramic industries)and farms are identified as the drivers of environmental issues.Citizen believed that environmental issues mainly affect human well-being.Moreover,the keywords of“odor”,“report”,“request”,“presence”,“municipality”,and“hours”were the most influential and meaningful concepts,as demonstrated by their high degree and betweenness centrality values.Keywords connecting odor(classified as impacts)and air pollution(classified as state)were the most important(such as“odor-burnt plastic”and“odor-acrid”).Complainants perceived odor annoyance as a primary environmental concern,possibly related to two main drivers:“odor-factory”and“odorsfarms”.The proposed approach has several theoretical and practical implications:text mining may quickly and efficiently address citizen needs,providing the basis toward automating(even partially)the complaint process;and the DPSIR framework might support the planning and organization of information and the identification of stakeholder concerns and priorities,as well as metrics and indicators for their assessment.Therefore,integration of the DPSIR framework with the text mining of environmental complaints might generate a comprehensive environmental knowledge base as a prerequisite for a wider exploitation of analysis to support decision-making processes and environmental management activities.
基金financially supported by the National Natural Science Foundation of China(Nos.72174158 and 72474164)the Fundamental Research Funds for the Central Universities of China(No.2042023kf0222)
文摘Rapid urbanization has markedly affected urban ecosystem health(EH),making it imperative to explore the relationships between EH and urbanization,as well as to identify the key factors influencing EH.This study addresses 2 key research gaps:(a)The traditional pressure–state–response evaluation framework fails to integrate ecosystem service demands and landscape pattern indices and has not formed a comprehensive EH evaluation system.(b)There is a lack of research on investigating the drivers and thresholds of EH across the areas in different spatial relationship between urbanization and EH at the urban scale.Here,taking Wuhan,China,as an example,this study assesses EH utilizing an optimized pressure–state–response evaluation framework.Additionally,bivariate Moran’s I is used to analyze the spatial relationship between EH and urbanization.We use gradient boosting decision trees to flexibly model the nonlinear relationships between influencing factors and EH,while Shapley additive explanations quantify each factor’s contribution,enhancing model interpretability and clarifying their effects on EH.The findings reveal a spatial distribution pattern characterized by lower EH levels in central areas and higher EH levels in periphery areas,with a notable negative spatial correlation between EH and urbanization.The spatial heterogeneity and clustering of EH and urbanization across Wuhan exhibit a ringlike pattern radiating from the center to the periphery.Landscape pattern index and land use are identified as key influencing factors of EH in Wuhan,with substantial regional variation,necessitating targeted environmental protection strategies.This study offers insights into urban planning and policymaking,promoting sustainable urban development.
