Environmental Policy Decisions Research Articles

Multi-classification prediction of PM2.5 concentration based on improved adaptive boosting rotation forest

Developing efficient, stable, and user-friendly methods and technologies for predicting air quality has contributed to environmental research and management. Most traditional machine learning (ML) models often struggle to efficiently process extensive air quality data and grapple with the challenge of imbalanced data distributions. To this end, we introduced a novel multi-strategy collaborative approach that incorporates weighted feature selection, an adaptive enhanced rotation forest algorithm, and Bayesian Optimization for parameter tuning. Moreover, to improve the transparency in black box ML models, the novel Shapley Additive Explanations (SHAP) method was applied to interpret the outputs and analyze the importance of individual variables. Through experiments on real air quality datasets, we have verified the accuracy of our proposed method in classifying air quality levels. Notably, our model demonstrated an average test set accuracy improvement of approximately 10 % in cities like Beijing, Tianjin, Shijiazhuang, and Baoding after hyperparameter optimization using Bayesian methods. Furthermore, compared to alternative algorithms, our model showed an improvement of 1–2 % in evaluation metrics. By introducing novel methodologies and tools, our research contributes significantly to the advancement of air quality classification technology and holds profound implications for informing environmental policy decisions.

A critical cognitive analysis of Japan’s nuclear contaminated water discharge discourse

This research investigates the use of compound image schemas in the discourse surrounding Japan’s nuclear wastewater discharge. By analyzing editorials from Asahi Shimbun, this study reveals how discourse producers, from government bodies to media outlets, employ image schemas to navigate, shape, and legitimize their stances on this contentious issue. The investigation identifies the prevalent use of PATH and CONTAINER schemas, facilitating the construction of complex narrative spaces that define “in-group” and “out-group” dynamics, thereby guiding public perception and discourse participation towards an implicit endorsement of specific policy directions. The findings highlight the dynamic interplay between micro-level discourse strategies and macro-level cognitive frameworks, projecting tailored narratives into the public sphere. This projection, rooted in sophisticated cognitive mechanisms, illustrates the strategic use of discourse to influence public opinion and legitimize environmental policy decisions, reflecting broader social implications and the power of discourse in shaping environmental risk perceptions.

Occurrences Status of Biota in Gochang-gun, South Korea

The Gochang-gun biotope map was used as a benchmarking model when preparing a county unit in the future, and was prepared for the purpose of constructing detailed spatial data for eco-friendly urban management and efficient management and value improvement of cultural assets. The purpose of this study is to provide data so that it is used as basic data for the distribution status of animals and plants and the systematic management of endangered wild animals. As a result of the survey of animals and plants in Gochang-gun, a total of 255 species of 88 families and 184 genera appeared. A total of eight families and 14 species of mammals appeared. A total of 32 families and 52 species of birds appeared. A total of nine and 26 species of fish appeared, and five species endemic to Korea appeared. Six and seven species of amphibians and reptiles appeared, respectively, and one species of exotic specices appeared. A total of 26 species of benthic large-scale vertebrates appeared, and three species endemic to Korea appeared. As for endangered wild creatures, two species of plants, six species of birds and three species of mammals appeared. It is judged that the data on animals and plants based on the urban ecological status map of Gochang-gun can be used as basic data for environmental policy decisions such as the management of ecosystem disturbances in Gochang-gun, the protection of endangered wild creatures, and the protection and restoration of plant and plant habitats.

The US Endangered Species Act and acceptable risk

The fundamental criterion for listing or delisting species under the United States Endangered Species Act (ESA) is acceptable extinction risk. But what is the meaning of “acceptable risk”? This concept has received little attention in conservation biology, and hence, the purpose of this paper is to explain acceptable risk within the context of the ESA. All complex environmental policy decisions involve trade-offs, and hence, choosing one policy from several policy options entails a comparison of the benefits, costs, and risks of all options. Acceptable-risk problems are decision problems requiring a choice among different policy options, and an acceptable risk is defined as the risk associated with the chosen policy. In general, people will accept the risk imposed by a particular policy when that policy yields sufficient net benefits. The ESA, its legislative history, and implementing regulations clearly state that species listing determinations must be based solely on science and “without reference to possible economic or other impacts” caused by the listing of that species. If economic considerations are prohibited from influencing listing decisions, then risk reduction is not constrained by cost, and therefore, the only rational choice for acceptable extinction risk is zero risk. This outcome, known as a “stopping-point problem”, is absurd, and consequently, federal agencies responsible for listing determinations are forced to issue opaque decisions that obscure their true rationale, which in turn, lead to inconsistency and improper political influence. Illustrations of acceptable risk in null hypothesis tests, the United States Clean Air Act, and minimum viable population size are also presented.

TEMDI: A Temporal Enhanced Multisource Data Integration model for accurate PM2.5 concentration forecasting

Accurate forecasting of PM2.5 concentration is crucial for implementing effective protective measures and mitigating the adverse health impacts of air pollution. To address the complex spatial propagation dynamics and temporal variations of PM2.5, we developed the Temporal Enhanced Multisource Data Integration (TEMDI) model. This innovative approach combines spatial modeling by a Graph Neural Network (GNN) to capture the intricate spatial propagation patterns based on multi-source data fusion, and a novel Time Series Enhancement (TSE) module that includes Ensemble Empirical Mode Decomposition (EEMD), Gated Recurrent Units (GRUs), and a self-attention mechanism to adequately manage the time series’ short-term and long-term trends. Our results demonstrate TEMDI’s superior performance, achieving exceptionally high Probability of Detection (POD) rates of 96.15%, 80.28%, and 71.86% for forecast horizons of 3, 36, and 72 h, respectively. Furthermore, our feature importance analysis reveals that multi-scale features extracted by the EEMD component become increasingly crucial as the prediction horizon extends. The TEMDI model’s ability to provide accurate, reliable PM2.5 forecasts and its enhanced interpretability position it as a valuable tool for guiding environmental policy and management decisions to safeguard public health.

The catalyzing role of financial inclusion in decoding environmental challenges and fostering a sustainable future in BRICS‐T

AbstractEnvironmental degradation poses a significant challenge globally, exhibiting diverse manifestations across regions and ecosystems. This study aims to decipher the factors contributing to environmental degradation, with a specific focus on Brazil, Russia, India, China, South Africa, and Türkiye countries, spanning the period of 1990–2018. This investigation revealed intricate interdependencies among financial institutions, market dynamics, energy utilization, demographic shifts, and ecological impacts. According to the findings of studies based on Durbin‐Hausman, Westerlund, CS‐ARDL cointegration, Juodis, Karavias, and Sarafidis and Dumitrescu‐Hurlin causality tests, policies that encourage financial inclusion and energy efficiency should be developed to prevent environmental degradation. On the other hand, attention has been given to the impact of population growth on environmental policy decisions. This research contributes valuable information to the ongoing discourse on the interrelationship between financial inclusion, the energy population, and environmental protection.

Life Cycle Sustainability Assessment of Waste to Energy Systems in the Developing World: A Review

The global move towards a circular economy, as well as that of achieving the United Nations Sustainable Development Goals (SDGs), has necessitated the search for several sustainable solutions in various sectors. Given this, the provision of sustainable waste management and electricity systems constitute a significant part of the SDGs, and the waste-to-energy (WtE) concept has recently become a key topic given that it can potentially help reduce the dependence on fossil fuels for energy generation, as well as minimizing the need to dispose of waste in landfill. However, to date, the sustainability assessments of WtE generation technologies have been limited in scope concerning the three-dimensional sustainability framework (economic, environmental, and social). Life Cycle Sustainability Assessment (LCSA) has been proposed as a potential approach that could comprehensively address these three pillars of sustainability simultaneously based on life cycle thinking. LCSA, as a holistic method, could also potentially deal with the complexity associated with decision-making by allowing for the consideration of a full range of possible sustainability consequences. LCSA is an analytical tool that integrates the Life Cycle Assessment (LCA), Life Cycle Costing (LCC), and Social Life Cycle Assessment (sLCA) methodologies, which already exist and continue to be developed. Individually, these life-cycle approaches tend to be used to point out particular ‘hotspots’ in product or service systems, and hence focus on direct impacts in a given sustainability domain, neglecting the indirect ones. LCSA aims for a more holistic sustainability perspective and seeks to address the associated challenge of integrating these three pillars of sustainability into an overall and more comprehensive sustainability assessment. This need for harmonization within the LCSA methodology is a major challenge in its operationalization. In recent years there has been steady progress towards developing and applying LCSA, including for WtE. The aim of this paper is to review the most recent trends and perspectives in developing countries, especially regarding how LCSA could help inform decision-making. The paper also analyses the LCSA literature to set out the theoretical and practical challenges behind integrating the three methods (LCA, LCC, and sLCA). The review was conducted via a search of keywords such as LCSA, waste, and energy in the Web of Science databases, resulting in the selection of 187 publications written in English. Of those, 13 articles operationalized LCSA in specific waste and WtE related case studies. The review provides a review of the application of LCSA for researchers, technological experts, and policymakers through published findings and identifies perspectives on new research. These include uncertainty, subjectivity in weighting, double-counting, the low maturity of sLCA, and the integration of the interconnection between the three dimensions (environmental, economic, and social dimensions) of LCSA results in decision-making. In addition, gaps (such as the integration of the interconnection between the three dimensions) that need to be addressed via further research are highlighted to allow for a better understanding of methodological trade-offs that come from using the LCSA analytical approach to assess the sustainability of WtE generation technologies, especially in developing countries. It is hoped that this study will be a positive contribution to environmental and energy policy decisions in developing countries faced with the dual problems of waste management and electricity supply along with their sustainable development goals.

Impact of the circular economy on waste management performance: The case of the environmental goods and services sector in South Korea

In South Korea, the Framework Act on Resource Circulation (FARC) was enacted in 2016, making the circular economy (CE) related data limited. This study examines waste management performance in South Korea from the perspective of waste reduction and recycling by using environmental goods and services sector (EGSS) data as a proxy for CE data to assess how adopting EGSS data in policies affects waste management. The current study assumes that the use of EGSS data for environmental policy decisions will result in less waste and increased recycling. To test this assumption, this study conducted a descriptive analysis and segmented linear regression using municipal solid waste (MSW) and EGSS data from 1986 to 2021. The results indicated that the adoption of EGSS data only positively affected the recycled amount and recycling rate of MSW, while its effects on the amount of generated and landfilled MSW was not significant.

The Long-Run Linkage among the Macroeconomic Factors and CO2 Emissions in terms of Sea Transport Induced EKC Hypothesis in USA

The main aim of this article is to comprehend the long-run relationship among sea transportation, energy use, GDP, and CO2 for USA from 1980 to 2023. In this sense, FMOLS, DOLS, CCR, and ARDL analyses are employed in order to investigate the entity of long-run linkage between the relevant variables. According to results of this manuscript, except energy use there is no both long-run relationship among variables and effects of independent variables (GDP, sea transportation) on dependent variable (CO2 emissions) from 1980 to 2023 in USA. Therefore, the sea transport-induced EKC hypothesis has not been confirmed empirically. Although the hypothesis has not been confirmed, there are some issues to consider in terms of energy consumption. Transportation energy consumption and greenhouse gas emissions are seen as an alarming threat to leaving a livable and sustainable green environment and economy to future generations. Fossil fuels used in transportation have an important place in carbon dioxide emissions. This is seen as a crucial environmental factor that all stakeholders should consider when planning energy and environmental policy decisions. In order to prevent environmental quality from being negatively affected by greenhouse gas and exhaust emissions, policy makers need to encourage more energy efficient and healthier transportation ways. Thus, the harmful effects of transportation energy consumption can be reduced as well.

Statistical analysis and water quality modeling towards holistic health assessment of Himalayan and peninsular rivers of India

Water occurs naturally in a variety of forms. Liquid water is present in rivers, lakes, the ground, the sea, and precipitation. The primary objective of water quality monitoring is to ascertain whether the water quality being observed is appropriate for its designated purposes. An investigation was undertaken to assess the concentration levels of various water quality parameters, including total hardness, electric conductivity, temperature, Ca, Cl, K, Mg, Na, SO4, and HCO3. The research assessed the physicochemical parameters of ten (10) rivers, including the following: Brahmaputra (Arunachal Pradesh); Barak (Assam); Godavari (Maharastra); Brahmani (Odisha); Sabarmati (Gujarat); Tapi (Gujarat); Mahi (Gujarat); and Ganga (Uttar Pradesh). Water samples were obtained from the aforementioned rivers spanning the years 2013 to 2020. Descriptive Analysis, one-way ANOVA, Covariance, and Correlation were utilized to examine the impact of the rate of change on the interrelationships among the parameters. At the current level, the Narmada River cannot meet the daily demands that arise during and after the monsoon. The primary sources of pollution were inputs from households, businesses, and agriculture. The Gang River portions have been poisoned by sewerages, untreated industrial discharges, and chemical surges from agricultural fields. The basin is still being impacted by a number of anthropogenic pressures associated with an expanding human population, such as changes in land use, elevated water pollution, increased water demand, river channelization, and the Brahmanputra River's regulating flow. Anthropogenic heavy metals Cu, Cd, Cr, Pb, and Ni have not been shown to exhibit seasonal changes; however, geogenic heavy metals Mn, Fe, Mg, and Ca have been recorded to undergo seasonal oscillations in the Barak River and Still. The alkaline impacts of the Godavari water sample on the river are shown by the physical-chemical analysis of the samples. The amount of dissolved oxygen has decreased at various sites when pollutants are added to the water. A rise in BOD and turbidity levels is a result of the introduction of contaminants at different sites. The tests of TDS and F-coli showed an increase in value because of the sewage and burial procedures. Reduced flows below the dam and sudden increases resulted in a significant loss of organisms due to water discharge for hydropower generation. The Krishna River lost several of its characteristic characteristics as a result of dams being built both upstream and downstream. The Brahmani River's summertime dissolved oxygen (DO) levels are found to vary from 6.16 to 7.81 mg/L. The Brahman River's water quality index varied from 36.7 to 44.1, which is considered excellent water quality. Huge public awareness, strong implementing environmental policy decisions are some of the potential solutions to increase the health conditions of the Himalayan and Peninsular rivers of India. India's Himalayan and Peninsular rivers' health is measured via water quality modeling. This study evaluates river health using physiochemical and biological parameters. This study examines Himalayan and Peninsular India's water resource management, environmental preservation, and public health.

Assessing Peru’s Land Monitoring System Contributions towards Fulfilment of Its International Environmental Commitments

Land use change (LUC) is recognized as one of the major drivers of the global loss of biodiversity and represents a major threat to ecosystems. Deforestation through LUC is mainly driven by fire regimes, logging, farming (cropping and ranching), and illegal mining, which are closely linked with environmental management policies. Efficient land management strategies, however, require reliable and robust information. Land monitoring is one such approach that can provide critical information to coordinate policymaking at the global, regional, and local scales, and enable a programmed implementation of shared commitments under the Rio Conventions: the United Nations Convention on Biological Diversity (CBD), Convention to Combat Desertification (UNCCD), and Framework Convention on Climate Change (UNFCCC). Here we use Peru as a case study to evaluate how a land monitoring system enables environmental policy decisions which appear in the country’s international commitment reports. Specifically, we synthesize how effective the ongoing land monitoring system has been in responding to current and future environmental challenges; and how improvements in land monitoring can assist in the achievement of national commitments under the Rio Conventions. We find that Peruvian policies and commitments need to be improved to be consistent with the 1.5 °C temperature limit of the Paris agreement. Regarding the Aichi targets, Peru has achieved 17% land area with sustainable management; however, the funding deficit is a great challenge. Even though Peru commits to reducing GHG emissions by reducing LUC and improving agricultural and land use forestry practices, it needs policy improvements in relation to land tenure, governance, and equity. Potential explanations for the observed shortcomings include the fragmentation and duplication of government roles across sectors at both a national and regional scale.

Histopathological effects of long-term exposure to realistic concentrations of cadmium in the hepatopancreas of Sparus aurata juveniles

In recent decades, cadmium has emerged as an environmental stressor in aquatic ecosystems due to its persistence and toxicity. It can enter water bodies from various natural and anthropogenic sources and, once introduced into aquatic systems, can accumulate in sediments and biota, leading to bioaccumulation and biomagnification in the food chain. For this reason, the effects of cadmium on aquatic life remain an area of ongoing research and concern. In this paper, a multidisciplinary approach was used to assess the effects of long-term exposure to an environmental concentration on the hepatopancreas of farmed juveniles of sea bream, Sparus aurata. After determining metal uptake, metallothionein production was assessed to gain insight into the organism's defence response. The effects were also assessed by histological and ultrastructural analyses. The results indicate that cadmium accumulates in the hepatopancreas at significant concentrations, inducing structural and functional damage. Despite the parallel increase in metallothioneins, fibrosis, alterations in carbohydrate distribution and endocrine disruption were also observed. These effects would decrease animal fitness although it did not translate into high mortality or reduced growth. This could depend on the fact that the animals were farmed, protected from the pressure deriving from having to search for food or escape from predators. Not to be underestimated is the return to humans, as this species is edible. Understanding the behaviour of cadmium in aquatic systems, its effects at different trophic levels and the potential risks to human health from the consumption of contaminated seafood would therefore be essential for informed environmental management and policy decisions.

Statistical analysis of seasonal variations in pollutant concentrations in urban atmosphere

In the context of global climate change and urbanization, the issue of air quality is becoming increasingly relevant. Air pollution poses a threat to human health and ecosystems, highlighting the need for monitoring the concentrations of pollutants. This study examines the seasonal variations in the concentrations of harmful substances in the urban atmosphere using statistical methods. The aim of the research is to analyze time series data on concentrations of carbon monoxide (CO), nitrogen oxide (NO), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), ammonia (NH3), and particulate matter (PM2.5 and PM10). Correlation and factor analysis are employed to assess the relationships between pollutants and identify underlying factors. The analysis of data collected over several years emphasizes seasonal changes, showing that pollutant concentrations are subject to significant fluctuations driven by both natural and anthropogenic factors. The results can be used to develop strategies for improving air quality and predicting the health impacts of pollution on the population. This research deepens the understanding of the dynamics of atmospheric pollution and its seasonal dependence, which is important for shaping environmental policy and management decisions.

Financial innovation, environmental degradation, and environmental Kuznets curve trends in China.

This study examines the environmental Kuznets curve (EKC) theory and its possible relevance in the context of China and the complex and one-of-a-kind interaction between financial innovation, environmental deterioration, and China. China's fast industrialization and consequent economic expansion have been accompanied by significant environmental difficulties, despite the country's status as the world's second largest economy. The research takes a secondary data approach to its investigation of this topic, drawing on a large dataset that spans many decades to ensure a thorough examination of the dynamic interaction between financial innovation and numerous environmental variables. The primary objective of this research is to determine whether or not recent developments in financial technology have contributed to the current trends of environmental degradation in China. In keeping with the central tenet of the EKC hypothesis, this study uses cutting-edge econometric techniques to investigate the existence of nonlinear correlations and inflection points. In addition, the research analyzes how policy interventions and regulatory measures have shaped the tendencies spotted. In elucidating the usefulness of financial innovation as a tool for promoting environmental betterment, this study's findings substantially contribute to the current discussion around sustainable development and economic policy. This research also carefully assesses the applicability of the EKC theory in China, providing insights that may be used to inform future environmental policy decisions. Ultimately, the success of measures to promote sustained economic growth and the preservation of the environment in China depends on an in-depth understanding of these delicate relationships. In addition, the lessons learned from this study have the potential to serve as a guide for economies facing similar difficulties.

Changing Patterns of Urban Green Spaces in Akure, Nigeria

Greenery and natural landscapes are vital to human well-being, especially in cities. Notably, the majority of people aspire to live in cities in search of opportunities and a better quality of life, which harms urban green spaces, also known as the "lungs of the city." Current debates on urban planning and sustainable development in Nigeria and around the world are fundamentally influenced by the rapid growth of urbanization and the ensuing domination of concrete spaces over natural spaces. This study examined patterns in Akure's urban green areas while taking into account the spatiotemporal pattern of vegetation cover between 1984 and 2022. The collected satellite imagery was analyzed using the ArcGIS application program, and the Normalized Difference Vegetation Index (NDVI) was used to calculate the rate and patterns of urban green space. Over time, changes in the spatial distribution of urban green spaces and the growth of non-green spaces were monitored and estimated. The depletion's implications for planning were addressed. To educate and inform urban residents about the protection, conservation, and preservation of natural landscapes within urban landscapes, it is thought that examining and analyzing the physical planning and environmental consequences of unchecked depletion of urban green spaces will be useful for making sustainable environmental policy decisions in harnessing the resources potentials.

Socioeconomic driving forces behind air polluting emissions in Mexico.

Air pollution is one of the most severe environmental problems that Mexico is currently facing. The objective of this paper is to quantify the most relevant socioeconomic driving forces behind air polluting emissions and, more specifically, 7 local pollutants in Mexico. We do so in a multilevel version of the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model that accounts for the spatial heterogeneity at the municipal level across the country. The results show that the most relevant variables to determine the emissions of atmospheric pollutants are the population, the harvested area and the number of cars, while technological development helps to mitigate such emissions. The ecological elasticities are, in all cases, smaller than one. Our purpose is to provide quantitative information about these socioeconomic driving forces of air deterioration as a basis to establish some recommendations for environmental policy decision-making.

Extinction risks and threats facing the freshwater fishes of Britain

Abstract Extinctions occur naturally in all environments, but rates have accelerated rapidly during the Anthropocene, especially in fresh water. Despite supporting many fish species of conservation importance, there has never been a formal assessment of their extinction risks in Britain, which has impeded their inclusion in relevant legislation and policy. This study therefore used the International Union for the Conservation of Nature (IUCN) Red List of Threatened Species™ Categories and Criteria to conduct the first systematic assessment of the extinction risks and threats facing the native freshwater and diadromous fishes of Britain. In addition, national assessments were produced for England, Scotland and Wales, reflecting the level at which environmental policy decisions are taken in Britain. Seven species were categorized as being threatened with extinction at the regional level, with European eel Anguilla anguilla and allis shad Alosa alosa classified as Critically Endangered, Atlantic salmon Salmo salar, vendace Coregonus albula and European whitefish Coregonus lavaretus classified as Endangered, and Arctic charr Salvelinus alpinus and twaite shad Alosa fallax classified as Vulnerable. In addition, burbot Lota lota was classified as Regionally Extinct, ferox trout Salmo ferox was categorized as Data Deficient, and 25 species were categorized as Least Concern. European sturgeon Acipenser sturio and houting Coregonus oxyrinchus, although probably native, qualified as only vagrants in fresh water, so were categorized as Not Applicable. The assessments provide objective baselines against which future changes can be determined, and a key evidence base to support policy and management decisions for the conservation of freshwater and diadromous fish species and their habitats in Britain. It is recommended that the assessments are repeated every 10 years, which would enable changes in conservation status, the effectiveness of policies and where targeted interventions may be required to be examined using the Red List Index.

Collaborative Alignment: a framework for community-based collaboration for natural resource management, environmental policy decisions, and locally-led climate action

This essay introduces the Collaborative Alignment Framework (CA) and proposes its suitability for empowering and engaging communities as they address issues related to SDG 15. The fifteenth Sustainable Development Goal is concerned with protecting, restoring and promoting sustainable use of terrestrial ecosystems; managing forests sustainably; combating desertification, and stopping and reversing land biodiversity loss. Doing so necessarily involves communities and the parties that have a lot at stake related to environmental safeguards and management practices. Consequently, the discussion of Collaborative Alignment occurs in the following steps: First, it situates CA in the community-based forest collaborative movement in the United States, a movement that emerged in the forestry sector in the 1990s. Second, the essay addresses the foundations of CA. Third, CA is explained. Fourth, case examples of CA applications are featured. Lastly, the essay presents the relevance of Collaborative Alignment to “locally-led adaptation”, a community and place-based approach for addressing climate change (and SDG 13).

Evaluating the Applicability of Global LULC Products and an Author-Generated Phenology-Based Map for Regional Analysis: A Case Study in Ecuador’s Ecoregions

An accurate and detailed understanding of land-use change affected by anthropogenic actions is key to environmental policy decision-making and implementation. Although global land cover products have been widely used to monitor and analyse land use/land cover (LULC) change, the feasibility of using these products at the regional level needs to be assessed due to the limitation and biases of generalised models from around the world. The main objective of the present study was to generate regional LULC maps of three target areas located in the main ecoregions of Ecuador at a resolution of 10 m using Google Earth Engine (GEE) cloud-based computing. Our approach is based on (1) Single Date Classification (SDC) that processes Sentinel-2 data into fuzzy rule-driven thematic classes, (2) rule refinement using Visible Infrared Imaging Radiometer Suite (VIIRS) data, and (3) phenology-based synthesis (PBS) classification that combines SDC into LULC based on the occurrence rule. Our results show that the three target areas were classified with an overall accuracy of over 80%. In addition, cross-comparison between the global land cover products and our LULC product was performed and we found discrepancies and inaccuracies in the global products due to the characteristics of the target areas that included a dynamic landscape. Our LULC product supplements existing official statistics and showcases the effectiveness of phenology-based mapping in managing land use by providing precise and timely data to support agricultural policies and ensure food security.

Valuing water quality in the United States using a national dataset on property values

High-quality water resources provide a wide range of benefits, but the value of water quality is often not fully represented in environmental policy decisions, due in large part to an absence of water quality valuation estimates at large, policy relevant scales. Using data on property values with nationwide coverage across the contiguous United States, we estimate the benefits of lake water quality as measured through capitalization in housing markets. We find compelling evidence that homeowners place a premium on improved water quality. This premium is largest for lakefront property and decays with distance from the waterbody. In aggregate, we estimate that 10% improvement of water quality for the contiguous United States has a value of $6 to 9 billion to property owners. This study provides credible evidence for policymakers to incorporate lake water quality value estimates in environmental decision-making.