Environment Canada Research Articles

Estimating methane emissions from the waste sector in southern ontario using atmospheric measurements

ABSTRACT We estimate methane emissions rates for urban waste treatment facilities from mobile in situ atmospheric concentration measurements using an inverse Gaussian plume methodology at facilities in Southern Ontario, Canada. We use these estimated emissions rates to investigate, update, and improve the existing high resolution methane inventories at the facility level for waste sources throughout the Greater Toronto Area and Southwestern Ontario. Our measurements encompass tens of thousands of kilometers worth of mobile survey data collected over 7 years, encompassing more than 650 downwind transects where we surveyed 14 active landfills, 11 closed landfills, 2 organic waste processing facilities, 3 open air windrow compost facilities, and 11 water resource recovery facilities across our study region. These sources account for 77% of the active landfills within Southern Ontario, which is estimated in inventories to be the largest source of methane emissions in the region. Within the Greater Toronto Area (GTA) megacity, the measured facilities represent about 52% of the total inventoried non-wetland methane emissions. We find that emissions from closed landfills are lower than inventory estimates, with significant implications for the methane budget in the GTA. We update the Facility Level and Area Methane Emissions for the GTA inventory with our measured emissions rates, which results in a 54% decline in the solid waste emissions, effecting a 35% lower estimate for the total anthropogenic methane emissions in the region. We attribute the bulk of this difference to a single facility: the Keele Valley landfill. Our atmospheric measurements also serve as a novel metric for evaluating the discrepancies between four facility level, and two high resolution gridded methane emissions inventories. Based on linear regressions of our measured emissions versus inventoried values, we find that the facility level first order decay model maintained by Environment and Climate Change Canada (ECCC) to be the most consistent with our measured emissions rates at landfills and the self-reported emissions to the Greenhouse Gas Reporting Program of ECCC to be the least consistent with our measurements.

THE IMPACT OF PROJECTED CANADIAN REGIONAL CLIMATE MODEL DATA ON FLEXIBLE PAVEMENT PERFORMANCE

This paper explores the impact of projected climatic loading parameters, utilizing Environment and Climate Change Canada (ECCC) data, on flexible pavement performance and design. Despite the expectation that flexible roads should endure various structural and environmental conditions throughout their design life, premature damage often occurs within the initial three to five years of service. Therefore, understanding the impact of climate change on flexible pavements in the historical, short, intermediate, and long term becomes crucial. The Pavement Mechanistic Empirical Design (PMED) was employed to assess climatic loading effects on pavement design and performance. PMED predicted rutting performances showed sensitivity when comparing historical and projected climatic loading files up to 2093. Preliminary results based on a 25-year design life for City of Windsor revealed a 72% higher rutting impact compared to historical data, shortening the pavement's design life by 28%, 56%, and 68% for short, intermediate, and long terms, respectively.

Building the foundation for polar bear science: Fifty years of research on polar bears in Western Hudson Bay

In 1966, Environment and Climate Change Canada (ECCC) (then Canadian Wildlife Service) initiated a research program on polar bears belonging to the Western Hudson Bay subpopulation (WH). This paper provides an overview of that program, highlighting the long-term research on WH polar bears with a focus on ECCC-led work. The WH research program, which has now extended across five decades with data on over 4600 individual bears, has evolved from a study of the basic ecology of polar bears into foundational work on the life history, demography, genetics, movement, behaviour, and ecology of an apex predator in a rapidly changing Arctic. Research on polar bears in Canada supports commitments under the Agreement on the Conservation of Polar Bears (1973), the Convention on Biological Diversity (1992), and Canada’s Species at Risk Act (2002). Among Canada’s 13 polar bear subpopulations, only WH has sufficient long-term monitoring of individuals to assess demographic, behavioural, and life history consequences of climate change and other anthropogenic stressors. Future research should continue to ask key questions on how long-term environmental changes impact the ecology of polar bears. Integrating community priorities into the research program is necessary for it to continue to be successful in the future.

Next-generation public health surveillance: extreme heat event prediction and monitoring system

Abstract Background Extreme Heat Events (EHEs) are a growing threat to public health. The increase in the frequency of occurrence of once rarer EHEs and the rise in their average temperatures are dangerously drastic for public health outcomes. Despite this, existing public health surveillance (PHS) systems fail to leverage IoT and AI technologies to facilitate real-time, continuous monitoring of EHE indicators and its associated health risks. This study closes this gap by proposing a comprehensive PHS system that can, in real-time monitor and predict EHE indicators to provide timely alerts to public health authorities. Methods The EHE PHS system collects EHE detection metrics, including indoor temperature and humidity levels, from IoT sensors and thermostats to map them across Canada, primarily focusing on low-income communities. The system also integrates historical climate data (surface temperature, humidity, wind speed and direction, and air quality indicators) from Environment Canada. The system uses the data to train initial prediction models including CNN, LSTM and GNN. The validated model will be integrated into the system, enabling real-time EHE prediction. The output will be displayed in user-friendly visualizations on the EHE PHS system’s dashboard capabilities. Results The system allows for the analysis of real-time data through dashboards and provides alerts when certain indicators (e.g. excessive or prolonged heat) detrimental to public health outcomes are detected. The alerts enable valuable lead time for public health authorities to implement proactive measures, such as issuing heat advisories and deploying resources to vulnerable areas. Conclusions The EHE PHS system will serve as a blueprint for global public health researchers, utilizing IoT and AI technologies for proactive crisis prevention. This knowledge will inform the development of heat-resilient policies and set a precedent for global public health crisis prevention. Key messages • The proposed EHE PHS system uses AI and IoT technologies, to enhance EHE prediction, risk identification, and real-time monitoring for effective public health interventions. • By integrating advanced predictive models and environmental data, the system facilitates early detection of EHE risk, which can significantly mitigate the health impact on vulnerable populations.

Aeolus Winds Improve Arctic Weather Prediction

AbstractIt has been proven that assimilating winds from the Aeolus global Doppler Wind Lidar (DWL) would enhance the predictive skill of weather forecast models. In this study, we use a series of observing system experiments to examine how currently assimilated “operational” wind products and Aeolus winds impact environment and climate change Canada's global forecast system over the data‐sparse Arctic region. Aeolus winds improve the tropospheric wind and temperature forecasts by about 0.7%–0.9% of error reduction (a 15%–20% effect compared to the impact of operational wind products) while having little impact on specific humidity. In particular, Aeolus winds have an impact on forecasts of strong wind days on the wind and temperature fields that is double the impact for weaker wind days. On the other hand, the operational wind products do not show as large a discrepancy in impact between forecasts of disturbed and normal days. These findings suggest significant potential for global DWL observations to enhance severe weather prediction in polar regions.

Rapid drops of ocean temperatures in several shallow bays in Nova Scotia during a recent cold air outbreak

Abstract From February 3-5, 2023 Atlantic Canada experienced an extremecold Arctic air outbreak with high winds that set many local meteor-ological records, including wind chills as low as -47°C. The impacts of the cold air outbreak on ocean temperatures and ice formation are investigated using predictions from the Coastal Ice-Ocean Prediction System for the East Coast of Canada (CIOPS-E), developed by Environment and Climate Change Canada. Observations from moorings further inform the predictions. The analysis suggests that during the event, several shallow bays and coastal areas in Nova Scotia experienced significant, abrupt temperature decreases ranging from 1.0 to 3.9°C. Overall cooling estimated by the model was 2.3°C for nearshore locations where observations recorded an average temperature decrease of 3.0°C. On the other hand, at individual sites the difference between observed and modelled cooling was up to 2.4°C. This difference can be attributed partly to the fact that the model does not adequately resolve the coastline features of some of the nearshore mooring sites. In comparison, we also analyze another cold air outbreak that occurred on December 15-18, 2016, with wind chills as low as -37°C. The ocean temperatures changes associated with this earlier event saw decreases of 0.8 to 3.5°C, potentially contributing to an ongoing fish kill in St. Mary’s Bay (near the mouth of the Bay of Fundy) at the time. Keywords: Ocean temperature, Cold air outbreak, Ocean forecasting, Shallow bays, Nova Scotia

Toxicological impacts of paper mill effluent on aquatic animals: A Review

Paper mill effluent is a complex mixture of chemicals, including pulping agents, bleaching agents, and other pollutants, which can harm aquatic life (Environment Canada, 2013). This review summarizes the toxicological effects of Paper mill effluent on aquatic animals, including fish, crustaceans, and molluscs.

A new high-resolution Coastal Ice-Ocean Prediction System for the East Coast of Canada

The Coastal Ice Ocean Prediction System for the East Coast of Canada (CIOPS-E) was developed and implemented operationally at Environment and Climate Change Canada (ECCC) to support a variety of critical marine applications. These include support for ice services, search and rescue, environmental emergency response and maritime safety. CIOPS-E uses a 1/36° horizontal grid (~ 2 km) to simulate sea ice and ocean conditions over the northwest Atlantic Ocean and the Gulf of St. Lawrence (GSL). Forcing at lateral open boundaries is taken from ECCC’s data assimilative Regional Ice-Ocean Prediction System (RIOPS). A spectral nudging method is applied offshore to keep mesoscale features consistent with RIOPS. Over the continental shelf and GSL, the CIOPS-E solution is free to evolve according to the model dynamics. Overall, CIOPS-E significantly improves the representation of tidal and sub-tidal water levels compared to ECCC’s lower resolution systems: RIOPS (~ 6 km) and the Regional Marine Prediction System – GSL (RMPS-GSL, 5 km). Improvements in the GSL are due to the higher resolution and a better representation of bathymetry, boundary forcing and dynamics in the upper St. Lawrence Estuary. Sea surface temperatures show persistent summertime cold bias, larger in CIOPS-E than in RIOPS, as the latter is constrained by observations. The seasonal cycle of sea ice extent and volume, unconstrained in CIOPS-E, compares well with observational estimates, RIOPS and RMPS-GSL. A greater number of fine-scale features are found in CIOPS-E with narrow leads and more intense ice convergence zones, compared to both RIOPS and RMPS-GSL.

A Real-World Analysis of Weather Variation on Disease Activity and Patient-Reported Outcomes in Psoriatic Arthritis.

Patients with inflammatory articular diseases, such as psoriatic arthritis (PsA), report weather changes in their symptoms. Our objective was to investigate the correlation between weather variation, disease activity (DA), and patient-reported outcomes (PROs) in patients with PsA. Hourly measurements of temperature, relative humidity, and pressure were obtained from 2015 to 2020 in Montreal (through Environment Canada) and were matched with DA and PROs of patients with PsA enrolled in Rhumadata. The differences in mean DA and PROs were examined between winter and summer. Pearson correlation coefficients were calculated between clinical profile and weather measurements. Among patients with PsA, 2665 PROs were collected for a total of 858 patients. The Clinical Disease Activity Index (P = 0.001) and Simplified Disease Activity Index (P < 0.001) were lower in winter. In summer, positive correlations were found between humidity and symptoms (using patient global assessment, fatigue, pain, C-reactive protein, Bath Ankylosing Spondylitis Disease Activity Index, Bath Ankylosing Spondylitis Functional Index), whereas negative correlations between temperature and Health Assessment Questionnaire-Disability Index were reported. In winter, positive correlations were observed between temperature, fatigue, and pain. This is the first study to investigate weather variations through subjective and objective PROs matched with patients with PsA. Statistically significant differences in clinical profile were evident between winter and summer, as well as in their correlation with weather measurements. However, these distinctions lack clinical significance, suggesting a small impact on patients with PsA.

The impact of climate variation on the spread of Shiga toxin-producing E. coli.

Shiga toxin-producing Escherichia coli (STEC) is influenced by seasonality, but there is limited understanding of how specific climatic variables contribute to disease spread. This information aids in understanding disease transmission dynamics and could potentially inform public health modeling. This retrospective cohort study analyzed public health data from Ontario, Canada, between 2012 and 2021, along with historical climate data from Environment Canada. We employed Seasonal Autoregressive Integrated Moving Average (S-ARIMA) models to assess how temperature and precipitation impact the incidence of STEC infections, measured per 10,000,000 population. The study included 1658 confirmed STEC cases. A significant correlation was found between STEC incidence and climatic variables. Each degree Celsius increase in maximum temperature was associated with a rise of 3 STEC cases per 10,000,000 population (Centers for Disease Control and Prevention (2024)). Additionally, each millimeter of increased precipitation correlated with an increase of 1.1 cases per 10,000,000 population. The findings demonstrate a significant impact of temperature and precipitation on STEC transmission, highlighting the importance of integrating meteorological data into public health surveillance. This integration may help inform public health responses and support healthcare systems in planning for future outbreaks. Further studies are needed to refine predictive models and develop effective early warning systems for clinical settings.

Towards a Canadian National River Water Quality-Modelling System: State of Science and Future Prospects

Water quality is of significant concern and ultimately critical to every Canadian’s quality of life and security. Canada has diverse and vast landscapes and stressors that impact various waterbodies differentially, with influencing factors including contaminant and nutrient loads from human activity (mining effluent, wastewater, agricultural runoff, plastics), landscape change (wetland drainage, urbanization) and climate change (warming water temperatures, longer open water seasons, extreme hydrological events, intensifying wildfires). Canadian rivers are especially important to the overall biogeochemistry, hydrology, biodiversity, and ultimate health of aquatic and terrestrial ecosystems. While each of Canada’s provinces and territories has extensive river water quality (physical, chemical, biotic) data and monitoring programs, Environment and Climate Change Canada coordinates various national programs that contribute to the collection and consolidation of these data and conducts extensive research into the study and modelling of key river water quality processes. Despite program-specific efforts, there remains poor capacity to predict current and future conditions in monitored and unmonitored Canadian rivers, particularly remote or northern rivers, due to a myriad of factors including lack of coordination amongst groups and examination of areas in which modelling efforts might be integrated. Herein, we review and analyse the current state of data availability, process studies, and modelling systems for Canadian river water quality. Our synthesis reveals that specific physical processes (water temperature, ice formation, permafrost thaw, sediment dynamics), biogeochemical processes (dissolved oxygen, dissolved organic matter, nutrient cycling, metals/contaminants) and ecological/biological features (biota mass, functional indicators) are well understood, though complex, and are amenable to empirical or mechanistic modelling. Review of this information assists us in identifying opportunities and challenges for developing a national water quality modelling system (NWQMS), that would eventually include similar modelling activities for parallel processes in lakes and integrated watersheds. We identify needs for stronger coordination of monitoring programs in remote areas, recommend use of novel remote sensing technologies, and development of a flexible, iterative ‘process’ for integrated modelling to which stakeholders beyond government can contribute. Such a platform would support short and long-term predictive models of Canadian water quality and ecosystem health, inform effluent concentration limits, and be an early warning system for source waters.

A new global daily sea‐surface temperature analysis system at Environment and Climate Change Canada

AbstractA new global daily sea‐surface temperature (SST) analysis system has been developed at Environment and Climate Change Canada (ECCC). All components of the new SST analysis system are implemented within the Modular and Integrated Data Assimilation System (MIDAS) software. MIDAS is already used for the data assimilation component of the main operational numerical weather prediction (NWP) systems at ECCC. The new SST analysis system, integrated together with the global sea‐ice analysis, will be part of the combined ocean surface analysis used for all operational prediction systems at ECCC. The data assimilation method used to compute the new SST analyses is two‐dimensional variational method with a diffusion operator for representing the horizontal background‐error correlations. A new algorithm for satellite data bias estimation has also been developed employing gridded bias estimates computed from a spatial averaging of the differences between collocated satellite and in‐situ data. New algorithms for quality control and thinning of satellite data have also been implemented, making each type of observational dataset more evenly distributed over the globe. The performance of the new SST system is examined relative to the current operational SST system by using independent data. The impact of using the new SST analysis within NWP and ocean prediction systems is also evaluated. When compared with the operational system currently in use, the experiments employing the new SST analysis system produce a nearly neutral impact on the NWP and ocean prediction systems. This validation of the new system is an important first step towards the ability to use MIDAS to perform ensemble‐based three‐dimensional ocean and coupled ocean‐ice–atmosphere data assimilation.

Fill‐spill‐merge terrain analysis reveals topographical controls on Canadian river runoff

AbstractDigital Elevation Models (DEMs) are a crucial tool for watershed analysis, offering valuable insights into landscape‐scale hydrology. Traditional watershed delineations are derived by filling a DEM to force flow paths through topographic depressions, thus creating a continuous drainage network throughout the domain. However, this approach is challenged in landscapes with abundant real‐world depression storage, intermittently flowing stream channels, and internally drained lake basin (endorheic basin) such as the Canadian Shield (CS). The CS landscape is characterized by “fill‐and‐spill” surface water hydrology, with runoff flow paths controlled by bedrock sills and rocky cascades that overtop when water levels are high but cease flowing when water levels are low. To better represent these intermittent drainage networks, we apply a non‐traditional, less‐aggressive DEM filling model (Fill‐Spill‐Merge or FSM) to a continental‐scale DEM (MERIT) all of Canada. To ensure adequate filling of DEM noise while also preserving real‐world topographic depressions, we propose a climatic method to initialize a key FSM parameter (“runoff depth”) that calibrates observed discharges from 1690 Environment and Climate Change Canada (ECCC) river gauges with climate model P‐ET (precipitation minus evapotranspiration) data. Our application of FSM to all 1690 gauged watersheds identifies 916 significant topographical control points controlling &gt;20% and/or 1000 km2 of their respective areas. The Geikie, Snare, Kazan, Tazin, and Seal rivers may be particularly affected, with impacted watershed areas ranging from 12% to 64%. Extending this approach to ungauged parts of the CS reveals an additional 635 significant topographical control points. Ensemble climate model projections suggest that around 10% of these control points are currently dry but will become active by 2100. This research explicitly determines how CS watersheds are affected by fill‐and‐spill hydrology, and demonstrates the importance of accurate terrain modelling for delineating surface water flow paths in depressional landscapes.

Spatial and Temporal Variation of Subseasonal-to-Seasonal (S2S) Precipitation Reforecast Skill across the CONUS

Abstract Precipitation forecasts, particularly at subseasonal-to-seasonal (S2S) time scale, are essential for informed and proactive water resource management. Although S2S precipitation forecasts have been evaluated, no systematic decomposition of the skill, Nash–Sutcliffe efficiency (NSE) coefficient, has been analyzed toward understanding the forecast accuracy. We decompose the NSE of S2S precipitation forecast into its three components—correlation, conditional bias, and unconditional bias—by four seasons, three lead times (1–12, 1–22, and 1–32 days), and three models, European Centre of Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction’s (NCEP) Climate Forecast System (CFS) model, and Environment and Climate Change Canada (ECCC), over the conterminous United States (CONUS). Application of a dry threshold, removal of grid cells with seasonal climatological precipitation means below 0.01 in. per day, is important as the NSE and correlations are lower across all seasons after masking areas with low precipitation values. Further, a west-to-east gradient in S2S forecast skill exists, and forecast skill was better during the winter months and for areas closer to the coast. Overall, ECMWF’s model performance was stronger than both ECCC and NCEP CFS’s performance, mainly for the forecasts issued during the fall and winter months. However, ECCC and NCEP CFS performed better for the forecast issued during the spring months and for areas further from the coast. Postprocessing using simple model output statistics could reduce both unconditional and conditional biases to zero, thereby offering better skill for regimes with high correlation. Our decomposition results show that efforts should focus on improving model parameterization and initialization schemes for climate regimes with low correlation.

In situ physiological and behavioural responses of vulnerable populations during an extreme heat event in Montreal, Quebec 2023: a pilot study

Introduction: Extreme heat events (EHE) continue to increase in frequency, intensity, and duration, posing a significant health threat to vulnerable populations. Despite the development of heat-health action plans, heat-related injuries during EHE persist with the majority occurring at-home. Although epidemiological evidence has identified vulnerable populations, limited evidence exists to confirm their physiological and behavioural responses within the natural environment. Objective: The objective was to undertake a pilot study to monitor heat-vulnerable populations before and during an EHE and determine whether differences in physiological strain, subjective sleep quality, thermal perception, and thirst, would be detected during the EHE. Methods: Five participants who identified as a member of at least one heat-vulnerable group (67±5 y, 84.3±18.0 kg) participated in this study which ran throughout the summer months in Montreal, Quebec 2023. Using HeatSuite, a multipoint remote data acquisition platform that captures indoor environmental conditions, participants continuously wore a fitness tracker, completed a daily sleep quality assessment and a short questionnaire 4 times a day to quantify their thermal sensation, thermal comfort, and thirst, and recorded their oral temperature, heart rate, and blood pressure at rest 3 times a day (morning, midday, and evening). An EHE, as defined by Environment Canada, occurred Sept. 5th – 7th (max ambient temperature: 30.6±0.6°C; max humidex: 40.7±0.6), and thus the physiological and behavioural data collected are compared to the 3 preceding days (Sept. 2nd – 4th, PRE; max ambient temperature 27.2±2.3°C; max humidex: 34.0±4.6). Results: While all participants had air-conditioning, mean indoor ambient temperature was slightly higher during the EHE (22.5±0.5°C) than PRE (21.4±0.6°C, P=0.03). Total step count increased during the EHE relative to PRE in 4 of 5 participants (+47±83%). Mean oral temperature was higher during the EHE (37.3±1.0°C) compared to PRE (36.7±0.7°C, p&lt;0.05). Mean heart rate was not different during the EHE (82±8 BPM) relative to PRE (81±7 BPM, P=0.32). Mean blood pressure was not different during PRE compared to during the EHE (P&gt;0.38). Subjective sleep quality was lower during the EHE compared to PRE (p&lt;0.05). Participants reported no difference in thermal discomfort (P=0.12) and sensation (P=0.38), however they reported an increased thirst sensation (P=0.03) during the EHE. Conclusion: This pilot study was successful at monitoring physiological and behavioural responses in situ of heat-vulnerable individuals during an EHE. The results suggest that the EHE reduced sleep quality, increased thirst and thermal sensations, resulted in a higher oral temperature, and that participants were more active during the EHE relative to the 3 preceding days. This research is supported by Dr. Ravanelli’s New Frontiers in Research Fund (NFRFR-2021-00247). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Assessing the influence of climate controls on grapevine biophysical responses: a review of Ontario viticulture in a changing climate

Climate change presents unique challenges for grape growers across the world. In Ontario, three distinct viticultural regions are experiencing climatic shifts towards warmer growing seasons. According to historical records collected from Environment and Climate Change Canada, Lake Erie North Shore has transitioned from an intermediate-to-warm growing season classification, the Niagara Peninsula from the lower to upper limits of the intermediate zone, and Prince Edward County from cool to intermediate, when analyzing their average growing season temperatures. Terroir is directly related to vine water status, an indicator of grapevine stress. Biophysical responses controlled by air temperature and precipitation include fluctuations in vapour pressure deficits, evapotranspiration, and water-use-efficiency rates, as well as soil water content levels. By conducting an extensive literature review, the development of a conceptual model addresses how variations in climatic controls, under the scope of climate change, may influence grapevine water status, biophysical responses, and associated production outcomes for Ontario vineyards. Cool-to-intermediate air temperatures, when paired with increased precipitation will lead to no or low vine stress, increasing photosynthesis and transpiration rates, and variable plant water-use-efficiency levels, producing higher yields and lower quality grapes, if no management strategies are applied. Oppositely, higher air temperature as a product of climate change, when paired with variable precipitation may produce mild-to-severe stress, reducing yield, and increasing grape quality. With the appropriate management strategies, both traditional and new, growers may be able to accommodate for the influence of climate change on their vineyards.

Implementation of All-Sky Assimilation of Microwave Humidity Sounding Channels in Environment Canada’s Global Deterministic Weather Prediction System

Abstract Cloud-affected microwave humidity sounding radiances were excluded from assimilation in the hybrid four-dimensional ensemble–variational (4D-EnVar) system of the Global Deterministic Prediction System (GDPS) at Environment and Climate Change Canada (ECCC). This was due to the inability of the current radiative transfer model to consider the scattering effect from frozen hydrometeors at these frequencies. In addition to upgrading the observation operator to RTTOV-SCATT, quality control, bias correction, and 4D-EnVar assimilation components are modified to perform all-sky assimilation of Microwave Humidity Sounder (MHS) channel 2–5 observations over ocean in the GDPS. The input profiles to RTTOV-SCATT are extended to include liquid cloud, ice cloud, and cloud fraction profiles for the simulation and assimilation of MHS observations over water. There is a maximum (35%) increase in the number of channel 2 assimilated MHS observations with smaller increases for channels 3–5 in the all-sky experiment compared to the clear-sky experiment, mostly because of newly assimilated cloud-affected observations. The standard deviation (stddev) of difference between the observed global positioning system radio occultation (GPSRO) refractivity observations and the corresponding simulated values using the background state was reduced in the lower troposphere below 9 km in the all-sky experiment. Verifications of forecasts against the radiosonde observations show statistically significant reductions of 1% in the stddev of error for geopotential height, temperature, and horizontal wind for the all-sky experiment between 72- and 120-h forecast ranges in the troposphere in the Northern Hemisphere domain. Verifications of forecasts against ECMWF analyses also show small improvements in the zonal mean of stddev of error for temperature and horizontal wind for the all-sky experiment between 72- and 120-h forecast ranges. This work was planned for operational implementation in the GDPS in fall 2023.

Exposure Assessment of Pesticides in Surface Waters of Ontario, Canada Reveals Low Probability of Exceeding Acute Regulatory Thresholds.

The objectives of this study were to: (1) characterize the exposure of aquatic ecosystems in Southern Ontario, Canada to pesticides between 2002 and 2016 by constructing environmental exposure distributions (EEDs), including censored data; and (2) predict the probability of exceeding acute regulatory guidelines. Surface water samples were collected over a 15-year period by Environment and Climate Change Canada. The dataset contained 167 compounds, sampled across 114 sites, with a total of 2,213 samples. There were 67,920 total observations of which 55,058 were non-detects (81%), and 12,862 detects (19%). The most commonly detected compound was atrazine, with a maximum concentration of 18,600 ngL- 1 and ~ 4% chance of exceeding an acute guideline (1,000 ngL- 1) in rivers and streams. Using Southern Ontario as a case study, this study provides insight into the risk that pesticides pose to aquatic ecosystems and the utility of EEDs that include censored data for the purpose of risk assessment.

Using emerging science to inform risk characterizations for wildlife within current regulatory frameworks.

Many jurisdictions have regulatory frameworks that seek to reduce the effects of environmental exposures of anthropogenic chemicals on terrestrial wildlife (i.e., mammals, birds, reptiles, and amphibians). The frameworks apply for new and existing chemicals, including pesticides (prospective assessments), and to environmental contamination from releases (retrospective risk assessments). Relatively recently, there have been many scientific advances that could improve risk estimates for wildlife. Here, we briefly describe current regulations from North America (United States and Canada) and from Europe that include risk assessments for wildlife to ascertain whether they are conducive to the use of emerging science and new methods. We also provide examples where new and emerging science may be used to improve wildlife risk characterization and identify areas in need of future research. Integr Environ Assess Manag 2024;20:765-779. © 2024 His Majesty the King in Right of Canada and The Authors. Integrated Environmental Assessment and Management © 2024 Society of Environmental Toxicology & Chemistry (SETAC). Reproduced with the permission of the Minister of Environment and Climate Change Canada. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Microparticles in Wild and Caged Biota, Sediments, and Water Relative to Large Municipal Wastewater Treatment Plant Discharges.

Anthropogenically modified microparticles including microplastics are present in municipal wastewater treatment plant (WWTP) effluents; however, it is unclear whether biotic exposures are elevated downstream of these outfalls. In the fall of 2019, the present study examined whether microparticle levels in resident fish, environmental samples, and caged organisms were elevated near the Waterloo and Kitchener WWTP outfalls along the Grand River, Ontario, Canada. Wild rainbow darters (Etheostoma caeruleum) were collected from a total of 10 sites upstream and downstream of both WWTPs, along with surface water and sediment samples to assess spatial patterns over an approximately 70-km river stretch. Amphipods (Hyalella azteca), fluted-shell mussels (Lasmigona costata), and rainbow trout (Oncorhynchus mykiss) were also caged upstream and downstream of one WWTP for 14 or 28 days. Whole amphipods, fish digestive tracts, and mussel tissues (hemolymph, digestive glands, gills) were digested with potassium hydroxide, whereas environmental samples were processed using filtration and density separation. Visual identification, measurement, and chemical confirmation (subset only) of microparticles were completed. Elevated abiotic microparticles were found at several upstream reference sites as well as at one or both wastewater-impacted sites. Microparticles in amphipods, all mussel tissues, and wild fish did not show patterns indicative of increased exposures downstream of effluent discharges. In contrast, elevated microparticle counts were found in trout caged directly downstream of the outfall. Across all samples, cellulose fibers (mainly blue and clear colors) were the most common. Overall, results suggest little influence of WWTP effluents on microparticles in biota but rather a ubiquitous presence across most sites that indicates the importance of other point and nonpoint sources to this system. Environ Toxicol Chem 2024;43:1047-1061. © 2024 His Majesty the King in Right of Canada and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Reproduced with the permission of the Minister of Environment and Climate Change Canada.