Implementation Of Mitigation Measures Research Articles

Enhancing Flood Risk Management: A Comprehensive Review on Flood Early Warning Systems with Emphasis on Numerical Modeling

During recent decades there has been an increase in extreme flood events and their intensity in most regions, mainly driven by climate change. Furthermore, these critical events are expected to intensify in the future. Therefore, the improvement of preparedness, mitigation, and adaptation counterparts is mandatory. Many scientific fields are involved in this task, but from a meteorological and hydrological perspective, one of the main tools that can contribute to mitigating the impact of floods is the development of Early Warning Systems. In this sense, this paper presents a scientific literature review of some of the most representative Flood Early Warning Systems worldwide, many of which are currently fully operational, with a special focus on the numerical modeling component when it is developed and integrated into the system. Thus, from basic to technically complex, and from basin or regional to continental or global scales of application, these systems have been reviewed. In this sense, a brief description of their main features, operational procedures, and implemented numerical models is also depicted. Additionally, a series of indications regarding the key aspects of the newly developed FEWSs, based on recent trends and advancements in FEWSs development found in the literature, are also summarized. Thus, this work aims to provide a literature review useful to scientists and engineers involved in flood analysis to improve and develop supporting tools to assist in the implementation of mitigation measures to reduce flood damage for people, goods, and ecosystems and to improve the community resilience.

A Sand Boil Database for Piping Risk Management in the Po River, Italy

Sand boil formation at the toe of river embankments is the typical manifestation of the initiation and progression of an internal erosion process known as backward erosion piping, which is recognized to be a major concern in many river systems worldwide. In Italy, more than 130 sand boils have been detected along the Po River, many of them experiencing recurrent reactivations during high-water events. In recent years, as part of the activities of the European project LIFE SandBoil, the Italian authority responsible for flood protection and flood damage reduction along the Po River has implemented a GIS-based web application to catalogue the sand boils observed in its operating area. The resulting database allows keeping records of a comprehensive and varied set of information, in terms of predisposing factors, initiation conditions and surface effects. Taking as a reference a well-documented cross-section of the Po River prone to piping, this paper describes the main features of this versatile and flexible tool, whose long-term aim is to support vulnerability studies and the development of risk maps against piping. The database, which might also accommodate data from different river basins, is thus meant to help in flood risk management, by suggesting priorities for the implementation of mitigation measures and allowing the monitoring of intervention effectiveness.

Pathways towards net zero: Assessment of enablers and barriers in Nepal

Implementing mitigation measures to limit global temperatures to below 2 °C poses several challenges. Even though Nepal's global emission contribution remains minimal, the nation is committed to the net zero targets aligned with the Paris Agreement through Nationally Determined Contributions (NDC) and Long-Term Low greenhouse gas Emission Development Strategies (LT-LEDS) by 2045, where the biggest emitters like India, China and European Union (EU) aims to achieve net zero by 2070, 2060 and 2050 respectively. In this context, detailed and concrete insights on context specific factors that inhibit or enable Nepal’s mitigation measures to robust climate action are still at its infancy. We assessed the enablers and barriers to implementing mitigation measures across the energy, transport and forestry sectors. For this, an adapted version of the Intergovernmental Panel on Climate Change (IPCC’s) Feasibility Assessment Framework is used, with data triangulated through an extensive literature review, as well as qualitative data collected through semi-structured interviews with sector-specific experts (n = 25), policymakers (n = 15) and industry managers (n = 10). Our results indicated that geophysical and topographical barriers are relatively less prominent. However, the institutional capacity and governance, and cross-sectional coordination inhibit the implementation of mitigation measures. Addressing institutional barriers, such as policy gaps, regulatory frameworks, capacity building and coordination challenges, is essential for unlocking the full potential of enablers and overcoming obstacles. This research serves as a valuable guide for countries like Nepal, helping them gain insights into the challenges they may encounter on their journey to net zero targets

Assessment of gully erosion susceptibility using four data-driven models AHP, FR, RF and XGBoosting machine learning algorithms

Gully erosion is a significant global threat to socioeconomic and environmental sustainability, making it a widespread natural hazard. Developing spatial models for gully erosion is crucial for local governance to effectively implement mitigation measures and promote regional development. This study applied two machine learning (ML) models, RF and XGB, alongside an AHP-based multi-criteria decision method and FR bivariate statistics, to assess gully erosion susceptibility (GES) in the Kangsabati River basin in eastern India's Chotonagpur plateau fringe. A GIS database was created, incorporating recorded gully erosion incidents and 20 conditioning variables, which were evaluated for multicollinearity. These variables served as predictive factors for assessing gully erosion presence in the study area. The models' performance was evaluated using metrics such as RMSE, MAE, specificity, sensitivity, and accuracy. The XGB model outperformed the others, achieving a predictive accuracy of 90.22%. The study found that approximately 6.56% of the Kangsabati catchment is highly susceptible to gully erosion, with 12.39% moderately susceptible and 81.05% not susceptible. The XGB model had the highest ROC value of 85.5 during testing, indicating its superiority over the FR (ROC = 81.7), AHP (ROC = 79.8), and RF (ROC = 83.8) models. These findings highlight the XGB model's efficacy and potential for large-scale GES mapping.

An Approach of Multi Criteria Decision Making in Analyzing Rural Road Safety in Nashik District

Abstract: Rural road safety evaluations play a significant role in the transportation industry, and most fatal accidents happen on these types of roads. Road Safety Analysis (RSA), a process to evaluate a road's safety criteria and support overall road management decision-making, ensures the avoidance of loss of life and property damage. The "Pradhan Mantri Gram Sadak Yojana," which is primarily utilized in rural areas, is the main emphasis of this. In order to identify the most vulnerable roadways and implement mitigation measures, roads must be prioritized depending on safety ratings. This document presents the results of a study conducted to rank the safety criteria of Pradhan Mantri Gram Sadak Yojana (PMGSY) roads, a particular category of rural roads. A questionnaire survey was used for the study's analysis, and three MCDM methods were used to examine the relationships and interactions between the various factors. The study's findings indicated that the based on input from PMGSY engineers and contractors. From the perspective of the engineers in the Nashik area, we can determine the safety impact factor that influences the safety assessment of the PMGSY route.

Managing Rockfall Hazard on Strategic Linear Stakes: How Can Machine Learning Help to Better Predict Periods of Increased Rockfall Activity?

When rockfalls hit and damage linear stakes such as roads or railways, the access to critical infrastructures (hospitals, schools, factories …) might be disturbed or stopped. Rockfall risk management often involves building protective structures that are traditionally based on the intensive use of resources such as steel or concrete. However, these solutions are expensive, considering their construction and maintenance, and it is very difficult to protect long linear stakes. A more sustainable and effective risk management strategy could be to account for changes on rockfall activity related to weather conditions. By integrating sustainability principles, we can implement mitigation measures that are less resource-intensive and more adaptable to environmental changes. For instance, instead of solely relying on physical barriers, solutions could include measures such as restriction of access, monitoring and mobilization of emergency kits containing eco-friendly materials. A critical step in developing such a strategy is accurately predicting periods of increased rockfall activity according to meteorological triggers. In this paper, we test four machine learning models to predict rockfalls on the National Road 1 at La Réunion, a key road for the socio-economic life of the island. Rainfall and rockfall data are used as inputs of the predictive models. We show that a set of features derived from the rainfall and rockfall data can predict rockfall with performances very close and almost slightly better than the standard expert model used for operational management. Metrics describing the performance of these models are translated in operational terms, such as road safety or the duration of road closings and openings, providing actionable insights for sustainable risk management practices.

Responding to and managing multijurisdictional outbreaks of COVID-19 in Canadian industrial worksite/work camp settings.

Early in the COVID-19 pandemic, the Public Health Agency of Canada(PHAC) and provincial/territorial(P/T) public health identified the need for a coordinated response to complex multijurisdictional COVID-19 outbreaks. The first large multijurisdictional industrial worksite COVID-19 outbreak highlighted the risk of transmission within these congregate work settings, the risk of transmission to the broader community(ies), and the need to develop setting-specific outbreak response frameworks. PHAC assembled a team to provide national outbreak support for multijurisdictional COVID-19 outbreaks in May 2020. The COVID-19 Outbreak Response Unit (ORU) worked with P/T partners to develop guiding principles for outbreak response and outbreak investigation processes, guidance documents, and investigation tools (e.g., minimum data elements and questionnaires). The ORU, P/T partners, and onsite industrial worksite health and safety staff leveraged outbreak investigation guidelines, industrial worksite outbreak process documents (including minimum data elements), and enhanced case questionnaires to respond to multiple COVID-19 outbreak investigations in industrial worksites. Clear roles/responsibilities and processes, along with standardized data, allowed for more efficient outbreak investigations and earlier implementation of mitigation measures. Multijurisdictional COVID-19 outbreaks highlighted the importance of public health collaboration with industry partners onsite. The assembly of a national outbreak response team was important to facilitate information sharing and provide technical support. Lessons learned and recommendations on outbreak preparation, detection, management, and communication are included to enhance a response framework applicable to future emerging or re-emerging pathogens with epidemic and/or pandemic potential.

International Law Review Of Space Debris Mitigation Efforts

Space debris has become an increasingly pressing issue in space exploration and utilization. This article conducts a comprehensive review of aspects of international law relating to space debris mitigation efforts. This research analyzes existing legal frameworks, including relevant multilateral treaties and international legal principles related to the space environment. With a focus on the principles of shared responsibility and avoidance of damage to the space environment, the study identifies key challenges in managing space junk and reducing the risk of collisions in earth orbit. An in-depth analysis of the role of national space agencies and international organizations in implementing mitigation measures was also carried out. In the context of international cooperation, this article evaluates existing collaborative efforts and proposes new measures to improve the effectiveness of space debris mitigation. A better understanding of legal responsibility and burden-sharing in addressing these issues became a central point in the study. By analyzing recent developments in space law and international environmental regulations, this article provides insight into the direction the global community might take in addressing future space debris mitigation challenges. It is hoped that this research can provide guidance for policymakers, academics, and legal practitioners in their efforts to maintain a clean and sustainable space environment.

Investigation of climate change impacts on daily streamflow extremes in Eastern Black Sea Basin, Turkey

This study was undertaken to evaluate how future uncertain climate-related hydrological responses and low and highflow frequencies affect local hydrology up to the 2100, depending on different Global Circulation Models (GCM) and different Concentration Scenarios (CS). To this end, daily total precipitation and daily mean temperature data were used for RCP4.5 and RCP8.5 CSs by employing GCMs (GFDL-ESM2M, HadGEM2-ES and MPI-ESM-MR). In the study, the years 1971–2000 were chosen as the baseline period. Future streamflow predictions were modeled by machine learning. The models were calibrated with baseline period data and future streamflow values were predicted by using the best Streamflow Prediction Model during the 2055s (2041–2070) and 2085s (2071–2100) periods. Flow Duration Curves from the streamflow predictions were obtained and by using them, discharges corresponding to 95% probability of exceedance for lowflow and 5% probability of exceedance for highflow were calculated. According to the findings, it is predicted that there will be decrease of approximately 21% in lowflow discharges and approximately 30% in highflow discharges. This prediction has suggested water resources managers to implement mitigation measures to climate change in Eastern Black Sea Basin and most probably in Türkiye, especially in the context of continuity of aquatic life and sustainable water supply. It is expected that the paper will take a very important place in estimating and evaluating the expected changes in basin hydrology in the coming years, especially in the highflows and lowflows, which are the key concepts in hydroelectric power generation and in flood management.

Distribution of microplastics in Lusi Island, Sidoarjo, Indonesia

Lusi Island, situated downstream of the Brantas River, is anticipated to harbour significant microplastics from Brantas River runoff. Consequently, a thorough analysis of the microplastic presence on Lusi Island is crucial for effective pollution mitigation. Despite the critical need for such investigations, more studies must report the abundance of microplastics in this locale. This study aims to fill this gap by examining the abundance of microplastics in the downstream area of the Brantas River, specifically Lusi Island. The research not only delves into the prevalence of microplastics but also investigates various water quality parameters, including dissolved oxygen, pH, temperature, turbidity, and total dissolved oxygen. The study reveals that the abundance of microplastics in Lusi Island ranges from 597 to 787 particles per litre in surface water samples. Three distinct types of microplastics—fragments, fibres, and film—were identified on the island. Notably, microplastic fragments dominate in number compared to other forms. Despite the favourable water quality parameters suggesting a healthy aquatic environment, the study underscores the necessity of implementing mitigation measures to address microplastic pollution effectively.

Assessing the probability of extremely low wind energy production in Europe at sub-seasonal to seasonal time scales

The European energy system will undergo major transformations in the coming decades to implement mitigation measures and comply with the Paris Agreement. In particular, the share of weather-dependent wind generation will increase significantly in the European energy mix. The most extreme fluctuations of the production at all time scales need to be taken into account in the design of the power system. In particular, extreme long-lasting low wind energy production events constitute a specific challenge, as most flexibility solutions do not apply at time scales beyond a few days. However, the probability and amplitude of such events has to a large extent eluded quantitative study so far due to lack of sufficiently long data. In this letter, using a 1000-year climate simulation, we study rare events of wind energy production that last from a few weeks to a few months over the January–February period, at the scale of a continent (Europe) and a country (France). The results show that the fluctuations of the capacity factor over Europe exhibit nearly Gaussian statistics at all time scales. A similar result holds over France for events longer than about two weeks and return times up to a few decades. In that case, the return time curves follow a universal curve. Furthermore, a simple Gaussian process with the same covariance structure as the data gives good estimates of the amplitude of the most extreme events. This method allows to estimate return times for rare events from shorter but more accurate data sources. We demonstrate this possibility with reanalysis data.

Pesticides in surface water of the Ondas river watershed, western Bahia, Brazil: Spatial-seasonal distribution and risk assessment

This study investigated the occurrence and seasonal distribution of different classes of pesticides in surface waters of the Ondas River Watershed, as well as potential risks to the aquatic health and human water consumption in the western region of Bahia state, Brazil. Two gas chromatography-mass spectrometry analytical methods were applied to monitor 34 pesticides in water samples collected during both the dry and rainy seasons at 17 sites. Upon individual analysis, only γ-HCH, methoxychlor, demeton-S, methyl parathion, fenitrothion, chlorpyrifos, and azoxystrobin exhibited statistically significant differences between seasons. During rainy season, concentration medians of residues were higher for γ-HCH (74.7 ng L−1), methoxychlor (25.1 ng L−1), and azoxystrobin (47.2 ng L−1), potentially linked to historical contamination or illegal use. Conversely, pesticides like methyl parathion, fenitrothion, and chlorpyrifos, belonging to the organophosphate class, showed higher concentration medians in the dry period, measuring 75.1, 5.50, and 10.8 ng L−1, respectively, probably due to region crop activities. The risk quotient (RQ) assessment for aquatic life indicated that 59.0% of the samples in the dry season and 76.0% in the rainy season had RQ values greater than one, signifying a critical scenario for species conservation. Regarding human consumption, elevated risks were observed for heptachlor in both sampling periods and for azoxystrobin during the rainy season, surpassing RQ levels above 1, indicating danger in untreated water ingestion. Additionally, 24.0% and 53.0% of the samples in the dry and rainy seasons, respectively, contained at least one pesticide exceeding the EU resolution limit (100 ng L−1). Therefore, considering this information, implementing mitigation measures to avoid the river's contamination becomes imperative.

Invasive New and Old World freshwater species in isolated springs of the Atacama Desert: implications for native species

ABSTRACT Invasive species can significantly alter invaded ecosystems. In this study, we report the presence of two invasive species, the poeciliid fish Poecilia reticulata and the gastropod Melanoides tuberculata, in three isolated springs from the coast of the Atacama Desert in Antofagasta city, northern Chile. Both species were identified through diagnostic morphological features and phylogenetic analysis. This is the first confirmed record of P. reticulata in natural ecosystems of Chile. The finding of M. tuberculata represents the first record of the species in the Antofagasta Region, and the third in the country. Considering the well-documented adverse effects of both species on invaded ecosystems and their high potential for spread, we recommend the prompt implementation of mitigation measures. These should focus on the direct mechanical removal of these species, given the relatively straightforward sampling process and the relatively small size of the springs. Such measures would significantly contribute to the preservation of native species, particularly those categorized as vulnerable.

Annual consumption and types of synthetic nitrogen fertilizers: Ammonia emission indicators for mitigation strategies in the European Union

Anthropogenic ammonia (NH3) emissions are primarily derived from agricultural activities. NH3 emissions from synthetic nitrogen (N) fertilizers are associated with the annual consumption of various N fertilizers. In this study, the annual consumption of different types of synthetic N fertilizers in the EU countries, derived from the database of the International Fertilizer Association, was analyzed, and the implementation of mitigation measures for NH3 emissions at the national level was assessed. NH3 emissions were estimated using the emission factors of different N fertilizers in cool, temperate, and hot climates and low- and high-pH soils, as the European Environment Agency proposed. The results revealed that the annual consumption of various synthetic N fertilizers (average values from 2016 to 2020) varied markedly in different EU countries. France, Germany, Poland, Spain, and the United Kingdom had the largest annual consumption of synthetic N fertilizers. NH3 emissions from urea-based fertilizers are the highest in most EU countries. The type of synthetic N fertilizer consumed contributed to the annual NH3 emissions. For example, although the annual synthetic N fertilizer consumption in Germany was 38% and 41.5% higher than those in Spain and Italy, the annual NH3 emissions in Germany were 63% and 20% lower than those in Spain and Italy, respectively, due to the high proportion of urea-based fertilizers with the highest emission factor among the synthetic N fertilizers in Spain and Italy. Thus, mitigation strategies should be tailored to specific types of N fertilizers with high emission factors and proportions to minimize NH3 emissions. Since the NH3 emissions from urea-based fertilizers are the highest in the EU countries, especially in the top five countries, we recommend the addition of urease inhibitors to urea fertilizers as one strategy for mitigating NH3 emissions.

Environmental Impact Assessment Follow–Up in Central Uganda’s Processing and Manufacturing Industries: Implications for Achieving Sustainable Development

Environmental impact assessment (EIA) was introduced in Uganda by the National Environment Act 1995, now repealed by the National Environment Act 2019. EIA was made operational by the EIA Regulations, 1998, which is now replaced by the National Environment (Environmental and Social Assessment) Regulations 2020. It is generally agreed that the EIA follow-up is an essential part of the EIA process, without which EIA becomes a pro-forma exercise seeking plan or project approval. This paper assesses the legal and regulatory provisions for EIA follow-up and the actual practice in central Uganda’s processing and manufacturing industries for 24 years (1995-2019) of practice. Data was collected from key categories of EIA stakeholders, including the affected public, the interested public, the developers, and the regulator or its delegated entities. Data was collected between 2018 and 2019 using a review of related literature, documentary analysis, checklists, key informant interviews, and specifically designed questionnaires for the different categories of key EIA stakeholders. Data was analyzed using largely descriptive statistics and, to some extent, inferential statistics. Our finding was that there was a wide gap between law and the actual practice of EIA follow-up. Specifically, there was limited monitoring by the regulator, absent post-assessment environmental audit, low to moderate implementation of mitigation measures and poor communication between the developers and the affected public. This was mainly due to poor implementation of the pre-approval phases of the EIA process and other context factors. The paper made several recommendations to improve the design and implementation of the EIA follow-up program

Enterprise Security as an Element of Market Competitiveness

The security of the enterprise is crucial for its competitiveness in the modern business climate. It involves the protection of assets, information, personnel, and business processes, including intellectual property. Insufficient protection can lead to the leakage of corporate information and infringement of patent rights, jeopardizing the competitiveness of the company. Focusing on security and implementing appropriate measures are essential for achieving market competitiveness and sustainability for the enterprise. The study pays attention to the complexity of defining suitable security measures for the enterprise, considering the dynamics of the environment, industry characteristics, and market presence. The aim of the research is to propose a competitiveness system focused on security, aiming to improve market position and enhance the sustainability of the enterprise. Proactively addressing threats and implementing mitigation measures are crucial for preventing uncertainty, ensuring the resilience of the enterprise, and preserving and increasing its competitiveness.

Stochastic modelling of pesticide transport to drinking water sources via runoff and resulting human health risk assessment

A modelling framework was developed to facilitate a probabilistic assessment of health risks posed by pesticide exposure via drinking water due to runoff, with the inclusion of influential site conditions and in-stream processes. A Monte-Carlo based approach was utilised to account for the inherent variability in pesticide and population properties, as well as site and climatic conditions. The framework presented in this study was developed with an ability to integrate different data sources and adapt the model for various scenarios and locations to meet the users' needs. The results from this model can be used by farm advisors and catchment managers to identify lower risk pesticides for use for given soil and site conditions and implement risk mitigation measures to protect water resources. Pesticide concentrations in surface water, and their risk of regulatory threshold exceedances, were simulated for fifteen pesticides in an Irish case study. The predicted concentrations in surface water were then used to quantify the level of health risk posed to Irish adults and children. The analysis indicated that herbicides triclopyr and MCPA occur in the greatest concentrations in surface water, while mecoprop was associated with the highest potential for health risks. The study found that the modelled pesticides posed little risk to human health under current application patterns and climatic conditions in Ireland using international acceptable intake values. A sensitivity study conducted examined the impact seasonal conditions, timing of application, and instream processes, have on the transport of pesticides to drinking water.

Drivers of spatio-temporal population dynamics of game species in a mountain landscape

Since the end of the nineteenth century, socio-economic changes have greatly altered the Central European landscape and the structural and functional quality of habitats. Urban sprawl areas have appeared, a reduction of multiple forest uses has resulted in the densification of forests and agricultural land use has changed fundamentally through specialisation and intensification. Many of these changes affect biodiversity. To determine the important drivers of spatio-temporal dynamics of the population of 28 game species, we first considered a total of 130 potential explanatory variables. Second, we aggregated the main drivers of single-species models for habitat guilds. Third, we evaluated the results to aid in the development and implementation of mitigation measures for different ecoregions. We used harvest data as a surrogate for population density from 1875 to 2014 in South Tyrol, Italy. In generalised linear models, we used environmental characteristics such as climate, landscape diversity and structures, land cover, hunting, wildlife diseases, competition and predation, land-use type, and intensity (including pesticide use) as explanatory variables to predict the spatio-temporal dynamics of game species. The important drivers are land use and management changes (intensification in the agriculturally favourable areas, extensification or abandonment in the unfavourable areas) as well as associated changes in the landscape features, diversity and structure, and hunting management. Climatic variables, interspecific competition and diseases only play a subordinate role. The dynamics of the habitat guilds and their drivers provide concrete indications for measures to maintain or improve the habitat quality for the investigated species. Particularly important are transfer payments to ensure extensive agricultural use, increasingly through the takeover of personnel costs, but also for the installation of an independent body that monitors and evaluates the effectiveness of the measures.

Impact of carbon pricing on mitigation potential in Chinese agriculture: A model-based multi-scenario analysis at provincial scale

China's ‘dual carbon’ goals seek to achieve peak CO2 emissions before 2030 and carbon neutrality before 2060. China is one of the world's largest emitters of agricultural greenhouse gases. Although existing studies have evaluated GHG mitigation potential in Chinese agriculture, few built models by incorporating socioeconomic conditions, technology diffusion, and carbon pricing policies. This study developed a bottom-up Agricultural Technology Optimisation Model (ATOM) for GHG mitigation, which selected optimal mitigation measure portfolios by minimising costs based on inventories of agricultural GHG and mitigation measures. It was employed to quantify long-term mitigation potential in Chinese agriculture under a range of socioeconomic and carbon pricing scenarios. GHG emissions in Chinese agriculture totalled 720.3 MtCO2e in 2017. Assuming an SSP2 scenario, the maximum technical mitigation potential of the evaluated measures in 2060 will be 554.1 MtCO2e, with 78.2% contributed by mitigation measures for crop production. 38.9% of this potential is possibly achievable with negative cost mitigation measures, and carbon pricing can help achieve greater emission reductions. Chinese agriculture theoretically possesses significant mitigation potential, but the implementation of mitigation measures may be hindered by multiple obstacles. The government should adopt counterstrategies to ensure that the agricultural sector remains on track to meet China's carbon neutrality goal.

Engaging urban residents in the appropriate actions to mitigate human–wildlife conflicts

AbstractMitigating human–wildlife conflicts by altering human behaviors is critical to urban wildlife conservation. We investigated what actions urban residents are willing to take to mitigate human–wildlife conflicts in metropolitan Atlanta, one of the fastest growing metropolises in the United States (~6.1 million people, 21,690 km2). In 2022, we administered online surveys to 1006 residents of metropolitan Atlanta to determine which measures they had adopted to mitigate conflicts with urban wildlife, elicit their stated willingness to adopt additional conflict mitigation measures, and identify determinants of current or potential implementation of mitigation measures. Respondents most frequently reported watching urban wildlife (63.0% of respondents). The most frequently reported conflicts were wildlife raiding trash cans (14.8%) and damaging landscaping (20.8%). In total, 342 respondents (34.0%) had not taken any action to mitigate conflicts with wildlife. Respondents who had taken action to prevent conflicts most often secured their trash by keeping cans indoors or locking the lid of the can (28.7%), kept pets (20.5%) and pet food (20.3%) indoors, and took trash out on the morning of collection (19.6%). Respondents who had not adopted conflict mitigation measures stated that they were likely to secure their trash or keep pets and pet food indoors if they considered these measures to be necessary. Prior conflicts with wildlife influenced both respondents' current efforts to mitigate conflicts with wildlife, and their stated willingness to adopt additional measures to mitigate human–wildlife conflicts. Risk sensitivity to zoonotic pathogen transmission increased both actual and intended adoption of conflict mitigation measures. Respondents' self‐efficacy, beliefs about wildlife, and age also influenced their willingness to adopt conflict mitigation measures. Our results suggest that education and outreach about the need for conflict mitigation measures should highlight the importance and effectiveness of these measures in conserving wildlife, while also securing the well‐being of humans and pets.