Urban Environmental Policy Research Articles

Why do we misperceive air pollution? A scoping review of key judgmental biases

AbstractAir pollution stands as a primary environmental factor influencing mortality globally. Despite its significance, individuals frequently struggle to assess the risks associated with polluted environments. This paper delves into the psychological mechanisms that contribute to the discrepancy between public perception of air quality and objective measurements. Through an extensive literature review spanning several decades, six fundamental heuristics that underpin misperceptions of air quality are identified and examined. The article further explores the theoretical and practical implications of acknowledging these biases in the development of urban environmental policies. By addressing judgmental biases, urban planners can improve the communication of risk information among lay people and ensure that environmental improvements are acknowledged and valued by all members of the community.

Nonlinear impacts of landscape and climatological interactions on urban thermal environment during a hot and rainy summer

Investigating the nonlinear impacts of urban landscape and climatic parameters on urban temperatures, a critical issue within urban climatology. Chengdu, characterized by its hot, rainy summers and rapid urban development, serves as an ideal model to illustrate these dynamics. Our investigation utilizes advanced analytical methods such as Random Forests (RF), SHapley additive explanation (SHAP), and Partial Dependence Plots (PDP) to analyze how landscape and climatic factors influence air temperature (AT) and land surface temperature (LST). Significant findings reveal profound thermal heterogeneity across Chengdu’s urban fabric, underscored by spatially distinct phenomena where some regions exhibit strong contrasts in temperature impacts due to varying climatic and landscape factors. The study identifies relative humidity and rainfall as key drivers of temperature variations during the summer months, reflecting Chengdu’s specific climatic idiosyncrasies. These insights are critical, as they highlight how urban planning and green infrastructure can be strategically used to mitigate adverse thermal effects. The research not only enhances understanding of the complex interplays within urban microclimates but also offers new perspectives on urban heat management. It contributes to the scientific community by providing evidence-based strategies for urban planners to counter the urban heat island effect and enhance urban resilience against climate change. This comprehensive analysis underscores the importance of incorporating multiple variables into urban climate models, lays the groundwork for more refined urban environmental policies and practices.

Barriers to equitable greening in urban environmental policies

ABSTRACT Histories of racist and classist land use decision-making have resulted in environmental disparities across lines of race and income in many U.S. cities. To redress this, many municipal governments are adopting urban greening initiatives that aim to provide public health benefits and bolster climate resilience in underserved communities. Unfortunately, increasing the quantity of green space in these areas does not necessarily mitigate disparities as environmental quality is just one factor in the broader challenges imposed by legacy land use decision-making. Green development in underserved neighborhoods has the potential to worsen social and economic equity concerns due to the influence of market forces. Employing a mixed-method approach encompassing policy review, spatial exploration, and qualitative interviews, this research examined the policies that guide urban greening decision-making in Philadelphia, Pennsylvania. Results indicate that Philadelphia faces a complex array of obstacles that inhibit equitable urban greening through four themes: (1) perceptions of agency responsibilities, (2) approaches to stakeholder engagement, (3) patterns of disinvestment and maintenance, and (4) project siting decisions. New policies and approaches are recommended to address these obstacles.

A cosine adaptive particle swarm optimization based long-short term memory method for urban green area prediction

In the quest for sustainable urban development, precise quantification of urban green space is paramount. This research delineates the implementation of a Cosine Adaptive Particle Swarm Optimization Long Short-Term Memory (CAPSO-LSTM) model, utilizing a comprehensive dataset from Beijing (1998–2021) to train and test the model. The CAPSO-LSTM model, which integrates a cosine adaptive mechanism into particle swarm optimization, advances the optimization of long short-term memory (LSTM) network hyperparameters. Comparative analyses are conducted against conventional LSTM and Partical Swarm Optimization (PSO)-LSTM frameworks, employing mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) as evaluative benchmarks. The findings indicate that the CAPSO-LSTM model exhibits a substantial improvement in prediction accuracy over the LSTM model, manifesting as a 66.33% decrease in MAE, a 73.78% decrease in RMSE, and a 57.14% decrease in MAPE. Similarly, when compared to the PSO-LSTM model, the CAPSO-LSTM model demonstrates a 58.36% decrease in MAE, a 65.39% decrease in RMSE, and a 50% decrease in MAPE. These results underscore the efficacy of the CAPSO-LSTM model in enhancing urban green space area prediction, suggesting its significant potential for aiding urban planning and environmental policy formulation.

Urban environment and unequal urban environmental policies: a case study in Argentina

Urban environment and unequal urban environmental policies: a case study in Argentina

Locating Electrified Aircraft Service to Reduce Urban Congestion

The relentless expansion of urban populations and the surge in e-commerce have increased the demand for rapid delivery services, leading to an increase in truck traffic that contributes to urban congestion, environmental pollution, and economic inefficiencies. The critical challenge this poses is not only in managing urban spaces efficiently but also in aligning with global sustainability goals. This study addresses the pressing need for innovative solutions to reduce reliance on truck transportation in congested urban areas without compromising the efficiency of freight delivery systems. This study contributes a novel approach that leverages electrified and autonomous aircraft (EAA) cargo shuttles to shift the bulk of air transportable freight from road to air, specifically targeting underutilized airports and establishing vertiports in remote locations. By applying data mining techniques to analyze freight flow data, this research identifies key commodity categories and metropolitan statistical areas (MSAs) where the implementation of EAA services could significantly mitigate truck-induced congestion. The findings reveal that targeting a select few commodities and MSAs can potentially decrease truck traffic, with electronics emerging as the dominant commodity category, and cities like Los Angeles and Chicago as prime candidates for initial EAA service deployment. Stakeholders in urban planning, transportation logistics, and environmental policy will find this study’s insights beneficial. This work lays a foundation for future innovations in sustainable urban mobility and logistics.

Exploring factors influencing user perspective of ChatGPT as a technology that assists in healthcare decision making: A cross sectional survey study.

As ChatGPT emerges as a potential ally in healthcare decision-making, it is imperative to investigate how users leverage and perceive it. The repurposing of technology is innovative but brings risks, especially since AI's effectiveness depends on the data it's fed. In healthcare, ChatGPT might provide sound advice based on current medical knowledge, which could turn into misinformation if its data sources later include erroneous information. Our study assesses user perceptions of ChatGPT, particularly of those who used ChatGPT for healthcare-related queries. By examining factors such as competence, reliability, transparency, trustworthiness, security, and persuasiveness of ChatGPT, the research aimed to understand how users rely on ChatGPT for health-related decision-making. A web-based survey was distributed to U.S. adults using ChatGPT at least once a month. Bayesian Linear Regression was used to understand how much ChatGPT aids in informed decision-making. This analysis was conducted on subsets of respondents, both those who used ChatGPT for healthcare decisions and those who did not. Qualitative data from open-ended questions were analyzed using content analysis, with thematic coding to extract public opinions on urban environmental policies. Six hundred and seven individuals responded to the survey. Respondents were distributed across 306 US cities of which 20 participants were from rural cities. Of all the respondents, 44 used ChatGPT for health-related queries and decision-making. In the healthcare context, the most effective model highlights 'Competent + Trustworthy + ChatGPT for healthcare queries', underscoring the critical importance of perceived competence and trustworthiness specifically in the realm of healthcare applications of ChatGPT. On the other hand, the non-healthcare context reveals a broader spectrum of influential factors in its best model, which includes 'Trustworthy + Secure + Benefits outweigh risks + Satisfaction + Willing to take decisions + Intent to use + Persuasive'. In conclusion our study findings suggest a clear demarcation in user expectations and requirements from AI systems based on the context of their use. We advocate for a balanced approach where technological advancement and user readiness are harmonized.

Built environment influences commute mode choice in a global south megacity context: Insights from explainable machine learning approach

In this study, we aimed to investigate the influence of the built environment (BE) on commuter mode choice using machine learning models in a dense megacity context. We collected 10,150 home-based commuting trips data from Dhaka, Bangladesh. We then utilized three machine learning classifiers to determine the most accurate prediction model for predicting the mode of transportation chosen for commuting in Dhaka. Based on the predictive performance of the classifiers, we identified that the Random Forest (RF) algorithm performed the best. Using the RF model, this study also explored the relative importance of BE factors in predicting commute mode choice, identified nonlinear relationships between the BE factors and mode choice, and examined the interaction effects of these factors on mode selection. Our results reveal that, compared to socio-demographic factors, the BE substantially influence commuter travel behavior. The BE characteristics have a specific nonlinear threshold limit at which they can have a notable impact on lowering private car use, and private car use does not display a constant return of scale with BE. Their interaction effects illustrate the potential optimal combination of BE interventions to lower private car use for commuting. These findings hold substantial implications for urban environmental policy, emphasizing the need for transit-oriented development, travel demand management, and integrated land-use transportation planning to foster low-carbon transportation systems in cities like Dhaka.

Spatio-temporal Landuse/Landcover Dynamics in the Coastal Areas of Limbe and Douala IV Municipalities and Implications on Wetland Regulating Ecosystem Services

Globally, wetlands are ecological hot spots and as a result they supply a plethora provisioning, regulating, supporting and cultural services. Despite their functions, wetlands continue to degrade arising from urban developments (population growth and housing developments, road infrastructural developments, urban agricultures and usage of wetlands as dumpsites). These activities operate via land use/land cover changes at different scales in different areas depending on technology and needs of the population. This paper describes the implications of spatio-temporal land use/ land cover (LULC) dynamics in the Limbe I and III Municipality (L1&3Ms) and Douala IV Municipality (D4M) coastal areas from 1986 to 2022 on wetland ecosystem services. This research made use of Geographic Information System (GIS) technique in describing the land use/cover changes in the study areas. Primary data was obtained through field observations, questionnaires and ground truthing aim at confirming the observations on downloaded satellite imageries. Four Satellite images of different years (1986, 1999, 2013 and 2022) were downloaded from the United State Geologic Survey (USGS) Earth Explorer. Images were imported into Erdas Imagine, 2014 where preprocessing was done and Supervised Classification was adopted for the processing of the image to generate a raster format depicting the designed land cover/land uses; especially the wetlands which constituted one of the themes. Maps were generated to show changes in land use/cover which were transposed into tables and figures to show the trends in magnitude of changes, percentage of change and the rate of change. Within 36 years (1986-2022) built-up increased by 0.75km2 (0.36%) and 1.63km2 (0.45%) while wetlands retreated by -0.2km2 (-.96%) and -0.48km2 (-0.14%) in L1&3M and D4M respectively. Annually, wetlands decreased by - 97.04km2 and -191.54km2 while settlements/infrastructures increased by 294.33km2 and 644.46km2 over the same 36 year periods in L1&3Ms and D4M respectively. Base on wetland regulating services, changes in LULC has exposes neighbourhoods in L1&3Ms to flood vulnerability comprising the vulnerable, less vulnerable, least vulnerable and most vulnerable areas as opposed to two categories of neighbourhoods in D4M (most vulnerable neighbourhood’s and the less vulnerable neighbourhoods). Information on changes in land use-land cover is crucial in delineating impacted areas, understand the type of changes, their spatial patterns and the need for formulating proper urban planning and environmental preservation policies as well as updating these policies with time. GIS analysis of 1986, 1999, 2013, and 2022, indicated that, there have been significant modifications in observed LULC classes (forest cover, farmland and built-up land uses) over L1&3Ms and D4M.

Discourse Studies, Corpus, and Multimodality in Urban Research

This paper explores the contribution of Discourse Studies (DS) to urban research from two perspectives: the field of inquiry and the research corpus. It investigates which areas have utilised DS in their research and why, as well as which types of discursive modes have been subjected to analysis. An analysis of 126 publications suggests that DS has been widely utilised to investigate urban questions in urban planning and theory, urban policy, housing research, and environmental policy; this capacity can be expanded to other fields of urban research. The study also finds out that the corpus of analysis has mainly remained monomodal, limited to one item or multiple items of the same type, predominantly text-based materials. To address this problem, the corpus of the analysis should be diversified to recognize the multimodality of discourse. This entails encompassing a variety of non-verbal modes such as images, music, gestures, moving images, soundtracks, and 3D objects. The paper concludes by pinpointing directions towards which future research should progress in order to overcome the challenges of utilising DS in urban research.Discourse Studies, Discourse, Urban Studies, Urban Research, Multimodality

Linking quality of life and sustainability in Canadian cities

In this study, we explore the relationship between urban quality of life and sustainability in 171 Canadian cities, each with a population of over 25,000. To do so, we built four indices—quality of life, socioeconomic sustainability, environmental sustainability, and a combined global sustainability index—to investigate factors that are associated with cities scoring above average on quality of life and sustainability indices. Our findings reveal a significant positive relationship between quality of life and all three sustainability indices. However, a weaker correlation between quality of life and the Environmental Index suggests potential shortcomings in urban environmental policies. Furthermore, disaggregated analyses enabled us to identify two significant factors influencing quality of life and both the global and socioeconomic sustainability indices: lower crime rates, which reflect safety and equity to some degree, and higher median incomes, which indicate the capability to afford a better standard and variety of goods and services. Notably, while certain indicators such as cultural expenditure, transit ridership, housing costs, city greenness, and waste production do not directly correlate with quality of life, their significance within the realms of socioeconomic and environmental sustainability suggests a long-term impact on quality of life. By improving sustainability through environmental and socioeconomic measures, city authorities can further enhance the quality of life for residents.

Analysis and Comparative Study of Signalized and Unsignalized Intersection Operations and Energy-Emission Characteristics Based on Real Vehicle Data

With the development of the economy, urban road transportation has been continuously improved, and the number of motor vehicles has also increased significantly, leading to serious energy consumption issues. As critical nodes in the urban road transportation network, intersections have become a focal point of research on vehicle energy consumption. To investigate whether traffic signal lights affect fuel consumption and emissions, this study analyzed the operating characteristics, fuel consumption, and emissions of intersections with and without traffic signal lights using real-world vehicle data. The data from the INTERACTION dataset for both signalized intersection VA and unsignalized intersection MA are used in the study, with a time duration of 3200 s. The VT-micro energy consumption and emissions model was applied to calculate and comprehensively analyze the vehicle flow, fuel consumption, and emissions. Additionally, the study compared the fuel consumption and emissions for different driving scenarios, including straight through, left turn, right turn, and U-turn, within a single traffic signal cycle. The results revealed that at signalized intersections, the average fuel consumption per vehicle was 26.54 L/100 km, NOx emissions were 68.76 g/100 km, and CO2 emissions were 61.07 g/100 km. In contrast, at unsignalized intersections, the average fuel consumption per vehicle was 46.88 L/100 km, NOx emissions were 149.26 g/100 km, and CO2 emissions were 107.16 g/100 km. The study indicated that for traffic volumes between 50 and 103 vehicles per 100 s, signalized intersections demonstrated better fuel consumption and emission performance than unsignalized intersections. Signalized intersections could accommodate larger traffic volumes and provide enhanced traffic safety. In conclusion, the findings of this study are important for urban traffic planning and environmental policies. They provide a scientific basis for reducing fuel consumption and emissions and improving road traffic efficiency. Due to the advantages of signalized intersections in terms of energy consumption and emissions, future urban traffic planning should consider more signal light controls to achieve energy savings, emission reduction, and improved traffic operation efficiency.

Reliability of smart noise pollution map

AbstractThe problem of noise pollution in Baghdad, the capital city of Iraq, is getting worse every day as a result of the increased volume of traffic. This presents a considerable risk, particularly on the main roads that connect densely populated neighborhoods such as the Al-Sadr City district with the central neighborhoods of the capital. In order to inform decision-makers in urban development and environmental policy about the high values of noise pollution that require remediation and regulation, noise maps are produced. However, two fundamental problems are generally faced in creating a more reliable noise map in the shortest possible time: the excessive time requirements for measuring noise and determining the method of map creation. Therefore, the role of geographic information system (GIS) software in producing noise maps is evident due to the difficulty of increasing the spatial density of measurements and integrating them with spatial information. Hence, an appropriate interpolation method is required. In this article, Moran’sIindex was calculated to assess the spatial autocorrelation of measured traffic noise points. A comparison was made between the Smart Map Plugin ordinary kriging (OK) and the inverse distance weighting (IDW) deterministic interpolation method to determine the best method for producing noise maps for the main entrance and exit roads of Al-Sadr City. The noise values were modeled using the best-performing method. Furthermore, the predictive raster data are displayed in the spatial context as a starting point and reference for identifying and understanding the levels of traffic noise in the selected study area. The locations of selected points for measuring traffic noise values were determined in an organized and homogeneous manner, where noise points for the main entrance and exit roads were opposite each other, and the distance between consecutive noise points on each road was 100 m. Traffic noise measurements were carried out at each selected point using the SVAN977 sound and vibration analyzer. At each measurement point, three noise values (LAeq, Max, Min) were obtained during the three peak times, 7–9 AM, 12–2 PM, and 4–6 PM. QGIS software was used to compare the two interpolation methods, with its strength lying in the use of plugins that facilitate spatial analysis, processing tools, and algorithms. The Smart Map Plugin provided facilities to choose the appropriate semi-variogram in the OK interpolation method. The root mean square error was used to compare the two interpolation methods in order to determine the most suitable method for producing traffic noise maps in the study area. The results indicated that the Smart Map Plugin using OK outperformed the IDW method, as spatial distribution pattern and homogeneity affect the accuracy of interpolation. Moreover, based on the analysis of the three noise attributes (LAeq, Max, Min), the performance of the Smart Map Plugin (OK) was found to be better than IDW when the Moran’sIvalue was high.

Preface

The first International conference on Design Innovations and Management for Sustainable Environment (ICDIMSE) was conducted on 15th and 16th March 2022 jointly by Sathyabama Institute of Science and Technology, India and Eastern Mediterranean University, North Cyprus held online in Zoom due to the COVID-19 pandemic. The conference aimed to bring together academicians, scientists, practitioners, researchers and students from a range of different disciplines to explore and share their experiences and research work in Sustainable Design of Built Environment. To prevent technical issues that can arise during the virtual mode of presenting, all the presentations of the accepted research papers were compiled beforehand which ensured a seamless conduct of the event by the participants who were from different parts of the world.Day 1 began with an opening session, which was followed by the keynote presenters Prof. DR. Shaleen Singhal, Dean (Research & Partnerships), TERI School of Advanced Studies, and Prof. Ali A. Alraouf (Associate AIA, Middle East and Gulf Chapter, Professor at HBK University in Qatar). Four parallel sessions that were moderated and chaired by DR. Monsingh David Devdas, Prof. Polat Hançer, Ar. Milon Dutta, and Prof. Illiona Outram followed the inaugural session.DR. Steffen Lehmann (Assoc. AIA, RIBA) and Prof. DR. Rohinton Emmanuel (Director of the BEAM Research Centre, Professor in Sustainable Design and Construction in Glasgow Caledonia University) delivered the keynote address on Day II of the conference. This was followed by four parallel sessions moderated and chaired by Tokie Laotan-Brown, DR. Abdul Razak, Yonca Hürol and DR.Swetha Madhusudhan. For all the eight sessions, best papers were awarded.Seventy nine research papers were presented during the conference under the themes: Design Innovations, Building Design and Performance Evaluation, Smart Materials and Artificial Intelligence, Sustainability in Architectural Design, Sustainable Design and Construction Processes, Urban Resilience, Safety, Disaster and Risk Mitigation, Sustainable Urban and Rural Development and Environmental Policy and Governance. The online conference was of great success having a diverse group of expertise and backgrounds with participants around the globe. This enabled a rich knowledge sharing environment with enthusiastic discussions.Forty of the conference papers were accepted for publication in the IOP EES Conference Proceedings. We express our gratitude to all the members who were a part of the peer review process and spent their valuable time in reviewing the papers.We express our deep gratitude to the Management of the Sathyabama Institute of Science and Technology and Eastern Mediterranean University, invited speakers, reviewers, and session chairs for their hard work along the series of conference events until this proceeding publication. We also thank all participants and authors for taking excellent opportunity for discussing and publishing the papers. We thank all the committee members and all those who have contributed for the success of ICDIMSE 2022 and publications of the Proceedings.List of Organising Committee, Executive Committee, Advisory Committee, Scientific Committee, Peer Review Committee, Technical Committee is available in the pdf.

Environmental advocates will monitor funding

“I think 2023 will be a very busy year,” says Robert Bullard, director of the Bullard Center for Environmental and Climate Justice. “Busy from the standpoint of building on some of the wins that we were able to achieve in 2022, particularly as it relates to getting environmental and climate justice integrated into federal policy, and making sure resources and funding follow those priorities.” Bullard, Distinguished Professor of Urban Planning and Environmental Policy at Texas Southern University, notes that federal funds and programs from President Joe Biden’s administration amount to a level of support that the environmental justice movement has never seen before. The $369 billion Climate Bill, part of the Inflation Reduction Act of 2022, for example, commits $60 billion to establishing grants and funding clean energy and environmental mitigation projects in disadvantaged communities. More broadly, the Biden administration has committed to channeling 40% of the benefits of relevant

Expansão urbana e ambiente nas gestões municipais de Vila Velha-ES entre 2009-2016

Abstract The paper aims to analyze the development of the urban environmental policy in the city of Vila Velha, state of Espírito Santo, during two municipal administrations between 2009 and 2016. It intends to investigate how the city, located in the Metropolitan Region of Grande Vitória, fills its urban environmental policy agenda, in an urban sustainability perspective, with elements of environmental justice and political ecology, based on the debate about ecocentric environmental rationality. The analysis focuses on the two municipal administration plans and on interviews with authorities who occupied relevant positions in Vila Velha, to investigate the concern about the way in which public administration deals with the disorganized occupation of the territory and with social conflicts in the distribution of the impacts of the environmental degradation on its urban environment.

Urban spatial structure and environmental efficiency: Empirical analysis from prefecture-level cities in China

China’s environmental problems are emerging with the continuous development of the economy and urbanization. The study of the impact of urban spatial structure on environmental efficiency has important significance concerning exploring ways to reduce the environmental cost of economic activity. Based on the fusion-corrected DMSP-OLS and NPP-VIIRS nighttime light data, this paper constructs spatial structure indicators of 276 prefecture-level cities and then empirically tests the impact of urban spatial structure on environmental efficiency using a fixed-effects model. The results show that: 1) The monocentric spatial structure has higher environmental efficiency than the polycentric spatial structure. 2) The mechanism analysis shows that the monocentric spatial structure could improve environmental efficiency through learning, sharing, and matching. 3) Population size and density have a robust moderating effect that when the resident population size of a city is more than 5 million or the population density is beyond 280 persons/km2, the monocentric spatial structure has a negative impact on environmental efficiency. In contrast, the polycentric spatial structure is more effective. 4) The point-based household registration policy adopted by the government to control population size has no significant impact on environmental efficiency, while the environmental information disclosure policy can effectively play a role. Our findings provide a basis for the Chinese government to formulate urban planning and environmental protection policies and offer the experience to other developing countries.

Development of urban air environmental control policies and measures

Development of urban air environmental control policies and measures

The Impact of Urbanization on CO2 Emissions in China: The Key Role of Foreign Direct Investment

ABSTRACT By adopting the dynamic panel threshold approach, this study assesses how foreign direct investment (FDI) shapes the causality between urbanization and CO2 emissions in China from 1996–2018. The results suggest that a rise in the pace of urbanization increases CO2 emissions, but this harmful effect becomes weaker after achieving a certain level of foreign capital. We also find that the more developed the technology, financial and government sectors, the more it can promote urbanization to reduce CO2 emissions. These results offer policy implications for China’s urban planning and environmental policy.

Public Acceptability of Environmentally Linked Congestion and Parking Charging Policies in Greek Urban Centers

Nowadays, urban centers face the challenge to upgrade life quality by reducing traffic congestion, air pollution emissions and road casualties. Transport charging policies applied in cities at a quick pace are a key tool for sustainable mobility. However, public acceptability is an important precondition to be adopted for such policies. In this context, the scope of this paper is the investigation of the public acceptability of environmentally linked urban charging policies in Greek urban centers. Specifically, the paper’s objective is the investigation of Greek drivers’ acceptability of the implementation of a congestion charging policy and a parking charging policy with the charging being adjusted according to the Euro class and technology of the vehicle in favor of less polluting cars. A structural equation model (SEM) was developed using data from a questionnaire survey which provided a sample encompassing 733 respondent drivers from three main urban centers of Greece: Athens, Thessaloniki and Volos. Several statistical relationships were detected and quantified correlating the two examined urban environmental charging policies with five latent unobserved variables. Based on the results, public acceptability of environmental congestion charging policies and the public acceptability of environmental parking charging policies were found to be positively correlated with each other, meaning that a driver who supports one environmentally linked transport charging policy is more likely to support the other one as well. The environmental sensitivity and high commuting profiles of drivers are influential factors that positively affect the acceptability of the two examined transport charging policies’ implementation in Greek urban centers. Analysis has also shown that younger, higher-educated respondents and females are more likely to accept the environmental charging policies under consideration.