Environment Canada Research Articles

The impact of new government childcare accreditation standards on children\u2019s in-care physical activity and sedentary time

BackgroundA new physical activity and sedentary behaviour accreditation standard criterion for childcare settings was introduced by the provincial government in Alberta, Canada. The primary objective of this study was to examine if changes for in-care physical activity and sedentary time (ST) differed between centres in and around Edmonton, Alberta after implementing the new accreditation standards and non-accredited control centres in and around Ottawa, Ontario. Secondary objectives were to examine whether baseline age group (toddler, preschooler) or the childcare environment moderated any group differences in change of the primary outcomes. Furthermore, accreditation and control group differences in change of children’s body mass index (BMI) Z-scores or cognitive development as well as educators’ perceptions of the primary outcomes were explored.MethodsParticipants were 252 toddlers (19–35 months) and preschoolers (36–60 months) in childcare centres from Alberta (n = 11) and Ontario (n = 8) in the supporting Healthy physical AcTive CHildcare setting (HATCH) study. In-care ST, light-intensity physical activity (LPA), and moderate- to vigorous-intensity physical activity (MVPA) were accelerometer–derived before and 6 months after the implementation of the new standards. At both time points, cognitive development (working memory, expressive vocabulary), heights, and weights were measured, and BMI Z-scores were calculated. Additionally, the childcare environment was observed using the Environment and Policy Assessment and Observation (EPAO) and Movement Environment Rating Scale (MOVERS) tools. Demographic characteristics were parent-reported and weather variables were derived from Environment Canada data. Mixed models were conducted.ResultsIn adjusted models (n = 241), change in children’s in-care ST (B = -0.07, 95%CI: − 1.43,1.29), LPA (B = 0.08, 95%CI: − 0.89,1.05), and log–transformed MVPA (B = 0.01, 95%CI: − 0.09,0.11) were not significantly different between accreditation and control groups. Age group and the childcare environment were not moderators. Significant increases in BMI Z-score (B = 0.19, 95%CI: 0.03,0.35) and high working memory (OR = 3.24, 95%CI: 1.32,7.97) were observed in the accreditation group and significant increases in expressive vocabulary (B = 3.18, 95%CI: 0.05,6.30) were observed in the control group.ConclusionsThe new accreditation criterion may not significantly change physical activity or ST in childcare settings and therefore may not explain findings for BMI Z-scores and cognitive development. Additional training and resources may be needed.

Air Quality Health Index in primary care: A feasibility study

Rationale: Exposure to poor air quality is associated with increased morbidity and mortality in patients with chronic obstructive pulmonary disease (COPD), asthma and heart failure. A number of countries, including Canada, report utilization of the Air Quality Health Index (AQHI) and associated health messages tailored to different AQHI categories for the public and at-risk populations to reduce exposure, adjust physical activity and optimize clinical management. Studies indicate AQHI advisories may not adequately reach or inform at-risk populations. Objectives: The objectives of this study were to design a text alert system and evaluate the feasibility of delivering AQHI forecast alerts to participants when AQHI readings exceeded low health risk. Secondary and tertiary objectives were to determine the frequency and accuracy of the alerts. Methods: Feasibility was assessed by the following steps: recruiting older adults with asthma, COPD and heart failure from primary care practices; developing software for extracting AQHI data from the Health Canada database; registering patients on the automatic dispatch messages system; and automatically sending AQHI forecast alerts of moderate health risk or above to participants’ cell-phones the preceding night. Results: We successfully queried the Environment Canada database, detected AQHI alerts and delivered them to participants. Forecast alerts of moderate health risk were higher in summer and winter 2018-2019 in the study areas. The accuracy of AQHI forecast alerts for North Toronto versus Downtown Toronto were 81.7% (75.9 − 86.6%) and 80.7% (74.8 − 85.7%), respectively. Conclusions: Delivering AQHI alerts through text messages to patients in the primary care setting was feasible. Colder seasons should not be underestimated for moderate risk AQHI conditions.

Interpolation of Precipitation Extremes on a Large Domain Toward IDF Curve Construction at Unmonitored Locations

An intensity–duration–frequency (IDF) curve describes the relationship between rainfall intensity and duration for a given return period and location. Such curves are obtained through frequency analysis of rainfall data and commonly used in infrastructure design, flood protection, water management, and urban drainage systems. However, they are typically available only in sparse locations. Data for other sites must be interpolated as the need arises. This paper describes how extreme precipitation of several durations can be interpolated to compute IDF curves on a large, sparse domain. In the absence of local data, a reconstruction of the historical meteorology is used as a covariate for interpolating extreme precipitation characteristics. This covariate is included in a hierarchical Bayesian spatial model for extreme precipitations. This model is especially well suited for a covariate gridded structure, thereby enabling fast and precise computations. As an illustration, the methodology is used to construct IDF curves over Eastern Canada. An extensive cross-validation study shows that at locations where data are available, the proposed method generally improves on the current practice of Environment and Climate Change Canada which relies on a moment-based fit of the Gumbel extreme-value distribution.

An automatic lake-model application using near-real-time data forcing: development of an operational forecast workflow (COASTLINES) for Lake Erie

Abstract. For enhanced public safety and water resource management, a three-dimensional operational lake hydrodynamic forecasting system, COASTLINES (Canadian cOASTal and Lake forecastINg modEl System), was developed. The modeling system is built upon the three-dimensional Aquatic Ecosystem Model (AEM3D) model, with predictive simulation capabilities developed and tested for a large lake (i.e., Lake Erie). The open-access workflow derives model forcing, code execution, post-processing, and web-based visualization of the model outputs, including water level elevations and temperatures, in near-real time. COASTLINES also generates 240 h predictions using atmospheric forcing from 15 and 25 km horizontal-resolution operational meteorological products from the Environment Canada Global Deterministic Forecast System (GDPS). Simulated water levels were validated against observations from six gauge stations, with model error increasing with forecast horizon. Satellite images and lake buoys were used to validate forecast lake surface temperature and the water column thermal stratification. The forecast lake surface temperature is as accurate as hindcasts, with a root-mean-square deviation <2 ∘C. COASTLINES predicted storm surges and up-/downwelling events that are important for coastal flooding and drinking water/fishery management, respectively. Model forecasts are available in real time at https://coastlines.engineering.queensu.ca/ (last access: January 2022​​​​​​​). This study provides an example of the successful development of an operational forecasting workflow, entirely driven by open-access data, that may be easily adapted to simulate aquatic systems or to drive other computational models, as required for management and public safety.

A One‐Dimensional Lake Model in ECCC's Land Surface Prediction System

AbstractIn most of Environment and Climate Change Canada's (ECCC) current operational systems, inland water physical processes are simulated using a simple water scheme. Water surface temperatures and ice cover fractions are updated daily using analyses. However, ECCC recognizes the need for interactive lakes in its weather and environmental prediction systems, such as those used to forecast surface conditions and floods. As a first step toward this goal, the current study evaluates the impact of the Canadian Small Lake Model (CSLM) in an offline context on surface water temperature, ice phenology and near‐surface atmospheric conditions. The use of CSLM increases lake surface temperatures and decreases its RMSE during ice‐free months, which has a direct impact on the 2‐m air temperature by reducing the cold bias observed in the simulation without CSLM, particularly over larger lakes. CSLM improves ice cover in subgrid lakes, while having a neutral impact on intermediate lakes. On large lakes, CSLM tends to degrade ice cover simulation in southernmost lakes, while improving ice cover in northernmost lakes. The increased lake ice cover in CSLM, particularly over subgrid lakes and in the northern latitudes, has a strong impact on humidity fluxes at the surface during wintertime with a near‐interruption of evapotranspiration over lakes. In summertime, increased water temperature with CSLM leads to a 38% increase in evapotranspiration. With these results, it is expected that the synergy of CSLM and lake‐related observations will improve the simulation and initialization of lake conditions in ECCC's systems.

Kejimkujik calibrated catchments: A benchmark dataset for long‐term impacts of terrestrial and freshwater acidification

AbstractDelays in forest recovery from terrestrial acidification combined with climate change are leading Acadian Forest ecosystems into new territory. The Kejimkujik Calibrated Catchments (KCC) Study Program was established in and adjacent to Kejimkujik National Park and Historic Site (KNP) in Southwest Nova Scotia (SWNS), Canada, in the late 1970s to study the impacts of acid precipitation on pristine and vulnerable ecosystems. The KCC now have one of the longest continuously monitored water chemistry records in North America, with data collection beginning in 1980. Its infrastructure includes three gauged streams with regular water chemistry sampling, 12 forest inventory plots, and an atmospheric deposition monitoring station. Recently, LiDAR data coverage was acquired for the study basins. Data collected at the KCC form part of the lake monitoring program of Environment and Climate Change Canada used in acidification, climate change, and mercury studies. Important characteristics of the KCC watersheds are their high sensitivity to acid deposition, high and increasing dissolved organic carbon (DOC) levels and lowland topography causing extensive wetlands. The KCC are also emerging as an important location for the study and protection of terrestrial and aquatic species‐at‐risk.

Developmental and Hepatic Gene Expression Changes in Chicken Embryos Exposed to p-Tert-Butylphenyl Diphenyl Phosphate and Isopropylphenyl Phosphate via Egg Injection.

Organophosphate flame retardants (OPFRs) are used in a variety of products such as clear coats, resins, and plastics; however, research into their toxicological effects is limited. p-Tert-butylphenyl diphenyl phosphate (BPDP) and isopropylphenyl phosphate (IPPP) are two OPFRs that were prioritized for whole-animal toxicological studies based on observed effects in cultured avian hepatocytes in a previous study. The present study investigates the toxicity of BPDP and IPPP in chicken embryos at different developmental stages by evaluating morphological and gene expression endpoints. Chicken eggs were exposed via air cell injection to 0-250 μg/g (nominal) of either compound and then artificially incubated. At day 11 (midincubation), liver samples were collected for mRNA expression analysis; and at day 20 (1 day prehatch), morphological measurements and liver samples for transcriptomic evaluation were collected. At 250 μg/g, gallbladder size was significantly reduced for both compounds, head/bill length and tarsus length were significantly decreased, and liver somatic index was significantly increased following IPPP exposure only. No effects on mortality were observed up to the highest administered concentration for either chemical. Using a ToxChip polymerase chain reaction array, we report significant differences in hepatic gene expression for both compounds and time points; the most pronounced transcriptomic effects occurred at midincubation. Genes related to xenobiotic metabolism, bile acid/cholesterol regulation, and oxidative stress were significantly dysregulated. Given these changes observed throughout avian embryonic development, further research into the long-term effects of BPDP and IPPP are warranted, especially as they pertain to liver cholestasis. Environ Toxicol Chem 2022;41:739-747. © 2021 Her Majesty the Queen in Right of Canada. Environmental Toxicology and Chemistry © 2021 SETAC. Reproduced with the permission of the Minister of Environment and Climate Change Canada.

Methane emissions in the United States, Canada, and Mexico: evaluation of national methane emission inventories and 2010–2017 sectoral trends by inverse analysis of in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) atmospheric observations

Abstract. We quantify methane emissions and their 2010–2017 trends by sector in the contiguous United States (CONUS), Canada, and Mexico by inverse analysis of in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) atmospheric methane observations. The inversion uses as a prior estimate the national anthropogenic emission inventories for the three countries reported by the US Environmental Protection Agency (EPA), Environment and Climate Change Canada (ECCC), and the Instituto Nacional de Ecología y Cambio Climático (INECC) in Mexico to the United Nations Framework Convention on Climate Change (UNFCCC) and thus serves as an evaluation of these inventories in terms of their magnitudes and trends. Emissions are optimized with a Gaussian mixture model (GMM) at 0.5∘×0.625∘ resolution and for individual years. Optimization is done analytically using lognormal error forms. This yields closed-form statistics of error covariances and information content on the posterior (optimized) estimates, allows better representation of the high tail of the emission distribution, and enables construction of a large ensemble of inverse solutions using different observations and assumptions. We find that GOSAT and in situ observations are largely consistent and complementary in the optimization of methane emissions for North America. Mean 2010–2017 anthropogenic emissions from our base GOSAT + in situ inversion, with ranges from the inversion ensemble, are 36.9 (32.5–37.8) Tg a−1 for CONUS, 5.3 (3.6–5.7) Tg a−1 for Canada, and 6.0 (4.7–6.1) Tg a−1 for Mexico. These are higher than the most recent reported national inventories of 26.0 Tg a−1 for the US (EPA), 4.0 Tg a−1 for Canada (ECCC), and 5.0 Tg a−1 for Mexico (INECC). The correction in all three countries is largely driven by a factor of 2 underestimate in emissions from the oil sector with major contributions from the south-central US, western Canada, and southeastern Mexico. Total CONUS anthropogenic emissions in our inversion peak in 2014, in contrast to the EPA report of a steady decreasing trend over 2010–2017. This reflects offsetting effects of increasing emissions from the oil and landfill sectors, decreasing emissions from the gas sector, and flat emissions from the livestock and coal sectors. We find decreasing trends in Canadian and Mexican anthropogenic methane emissions over the 2010–2017 period, mainly driven by oil and gas emissions. Our best estimates of mean 2010–2017 wetland emissions are 8.4 (6.4–10.6) Tg a−1 for CONUS, 9.9 (7.8–12.0) Tg a−1 for Canada, and 0.6 (0.4–0.6) Tg a−1 for Mexico. Wetland emissions in CONUS show an increasing trend of +2.6 (+1.7 to +3.8)% a−1 over 2010–2017 correlated with precipitation.

Development of aerosol optical properties for improving the MESSy photolysis module in the GEM-MACH v2.4 air quality model and application for calculating photolysis rates in a biomass burning plume

Abstract. The photolysis module in Environment and Climate Change Canada's online chemical transport model GEM-MACH (GEM: Global Environmental Multi-scale – MACH: Modelling Air quality and Chemistry) was improved to make use of the online size and composition-resolved representation of atmospheric aerosols and relative humidity in GEM-MACH, to account for aerosol attenuation of radiation in the photolysis calculation. We coupled both the GEM-MACH aerosol module and the MESSy-JVAL (Modular Earth Submodel System) photolysis module, through the use of the online aerosol modeled data and a new Mie lookup table for the model-generated extinction efficiency, absorption and scattering cross sections of each aerosol type. The new algorithm applies a lensing correction factor to the black carbon absorption efficiency (core-shell parameterization) and calculates the scattering and absorption optical depth and asymmetry factor of black carbon, sea salt, dust and other internally mixed components. We carried out a series of simulations with the improved version of MESSy-JVAL and wildfire emission inputs from the Canadian Forest Fire Emissions Prediction System (CFFEPS) for 2 months, compared the model aerosol optical depth (AOD) output to the previous version of MESSy-JVAL, satellite data, ground-based measurements and reanalysis products, and evaluated the effects of AOD calculations and the interactive aerosol feedback on the performance of the GEM-MACH model. The comparison of the improved version of MESSy-JVAL with the previous version showed significant improvements in the model performance with the implementation of the new photolysis module and with adopting the online interactive aerosol concentrations in GEM-MACH. Incorporating these changes to the model resulted in an increase in the correlation coefficient from 0.17 to 0.37 between the GEM-MACH model AOD 1-month hourly output and AERONET (Aerosol Robotic Network) measurements across all the North American sites. Comparisons of the updated model AOD with AERONET measurements for selected Canadian urban and industrial sites, specifically, showed better correlation coefficients for urban AERONET sites and for stations located further south in the domain for both simulation periods (June and January 2018). The predicted monthly averaged AOD using the improved photolysis module followed the spatial patterns of MERRA-2 reanalysis (Modern-Era Retrospective analysis for Research and Applications – version 2), with an overall underprediction of AOD over the common domain for both seasons. Our study also suggests that the domain-wide impacts of direct and indirect effect aerosol feedbacks on the photolysis rates from meteorological changes are considerably greater (3 to 4 times) than the direct aerosol optical effect on the photolysis rate calculations.

Ocean Surface Wind Speed Retrieval From the RADARSAT Constellation Mission Co- and Cross-Polarization Images Without Wind Direction Input

New techniques for automated retrieval of ocean surface wind speed from the RADARSAT Constellation mission (RCM) without input wind direction have been developed and tested. We collected a large number of collocated and coincided ocean buoy wind measurements and RCM co- and cross-polarization observations acquired over the West and East coasts of Canada from February 1, 2020 to July 25, 2021: 1190 data points for RCM ScanSAR 50 m (SC50M) VV–VH, 3819 points for SC50M HH–HV, and 397 points for ScanSAR Low Noise (SCLN) HH–HV images. The observations captured a wide range of wind conditions with the maximum wind speeds of 22.3, 23.8, and 19.7 m/s for SC50M VV–VH, SC50M HH–HV, and SCLN HH–HV, respectively. For these three types of RCM data, the ocean surface wind speed was modeled as a function of the co-polarization (VV or HH) and cross-polarization backscatter (VH or HV) as well as the noise floor and the incidence angle. The models were tested on completely independent subsets of data, and their performance was compared against CMOD5.N (for VV) and CMODH (for HH) models which require input wind direction. The root-mean square errors (RMSEs) for the proposed models in the testing subsets are 1.20, 1.52, and 1.26 m/s, while CMOD models showed 1.37, 1.91, and 3.06 m/s for SC50M VV–VH, SC50M HH–HV, and SCLN HH–HV, respectively. The proposed models are being integrated in various Environment and Climate Change Canada applications including ice and wind data assimilation systems and the National SAR Winds program.

Estimating 2010–2015 anthropogenic and natural methane emissions in Canada using ECCC surface and GOSAT satellite observations

Abstract. Methane emissions in Canada have both anthropogenic and natural sources. Anthropogenic emissions are estimated to be 4.1 Tg a−1 from 2010–2015 in the National Inventory Report submitted to the United Nation's Framework Convention on Climate Change (UNFCCC). Natural emissions, which are mostly due to boreal wetlands, are the largest methane source in Canada and highly uncertain, on the order of ∼ 20 Tg a−1 in biosphere process models. Aircraft studies over the last several years have provided “snapshot” emissions that conflict with inventory estimates. Here we use surface data from the Environment and Climate Change Canada (ECCC) in situ network and space-borne data from the Greenhouse Gases Observing Satellite (GOSAT) to determine 2010–2015 anthropogenic and natural methane emissions in Canada in a Bayesian inverse modelling framework. We use GEOS-Chem to simulate anthropogenic emissions comparable to the National Inventory and wetlands emissions using an ensemble of WetCHARTS v1.0 scenarios in addition to other minor natural sources. We conduct a comparative analysis of the monthly natural emissions and yearly anthropogenic emissions optimized by surface and satellite data independently. Mean 2010–2015 posterior emissions using ECCC surface data are 6.0 ± 0.4 Tg a−1 for total anthropogenic and 11.6 ± 1.2 Tg a−1 for total natural emissions. These results agree with our posterior emissions of 6.5 ± 0.7 Tg a−1 for total anthropogenic and 11.7 ± 1.2 Tg a−1 for total natural emissions using GOSAT data. The seasonal pattern of posterior natural emissions using either dataset shows slower to start emissions in the spring and a less intense peak in the summer compared to the mean of WetCHARTS scenarios. We combine ECCC and GOSAT data to characterize limitations towards sectoral and provincial-level inversions. We estimate energy + agriculture emissions to be 5.1 ± 1.0 Tg a−1, which is 59 % higher than the national inventory. We attribute 39 % higher anthropogenic emissions to Western Canada than the prior. Natural emissions are lower across Canada. Inversion results are verified against independent aircraft data and surface data, which show better agreement with posterior emissions. This study shows a readjustment of the Canadian methane budget is necessary to better match atmospheric observations with lower natural emissions partially offset by higher anthropogenic emissions.

Improving Snow Analyses for Hydrological Forecasting at ECCC Using Satellite-Derived Data

As part of the National Hydrological Services Transformation Initiative, Environment and Climate Change Canada (ECCC) designed and implemented the National Surface and River Prediction System (NSRPS) in order to provide surface and river flow analysis and forecast products across Canada. Within NSRPS, the Canadian Land Data Assimilation System (CaLDAS) produces snow analyses that are used to initialise the land surface model, which in turn is used to force the river routing component. Originally, CaLDAS was designed to improve atmospheric forecasts with less focus on hydrological processes. When snow data assimilation occurs, the related increments remove/add water from/to the system, which can sometimes be problematic for streamflow forecasting, in particular during the snowmelt period. In this study, a new snow analysis method introduces multiple innovations that respond to the need for higher quality snow analyses for hydrological purposes, including the use of IMS snow cover extent data instead of in situ snow depth observations. The results show that the new snow assimilation methodology brings an overall improvement to snow analyses and substantially enhances water conservation, which is reflected in the generally improved streamflow simulations. This work represents a first step towards a new snow data assimilation process in CaLDAS, with the final objective of producing a reliable snow analysis to initialise and improve NWP as well as environmental predictions, including flood and drought forecasts.

Assessment of metocean forecasts for Hurricane Lorenzo in the Azores Archipelago

This paper analyzes the performance of multiple wind and wave operational forecasts of Hurricane Lorenzo, the easternmost Category 5 Atlantic hurricane on record. Deterministic and ensemble forecast products from the National Centers for Environmental Prediction, Environment Canada's Meteorological Center, US Navy Fleet Numerical Meteorology and Oceanography Center, and Deutscher Wetterdienst have been selected for the assessment, which is based on in situ observations collected in the Azores Archipelago and satellite data (altimeters and scatterometers). Forecast ranges up to one week are analyzed and the error metrics are calculated as a function of the forecast lead times. The results show that the ensemble forecasts presented better performance than the deterministic forecasts, maintaining high correlation coefficients and low scatter indexes at longer ranges. However, the ensemble averages are associated with negative bias and increasing underestimation of the peak of the storm when the ensemble spread is large.

The Relationship between Clouds Containing Multiple Layers 7.5–30 m Thick and Surface Weather Conditions

Previous studies have identified finely laminated, or layered, features within Arctic clouds. This study focuses on quasi-horizontal layers that are 7.5 to 30 m thick, within clouds from 0 to 5 km altitude. No pre-selection for any particular cloud types was made prior to the identification of laminations. We capitalize on the 4-year measurement record available from Eureka, Nunavut (79.6∘ N, 85.6∘ W), using the Canadian Network for the Detection of Atmospheric Composition Change (CANDAC) Rayleigh–Mie–Raman Lidar (CRL; 1 min, 7.5 m resolution). Laminated features are identified on 18% of all days, from 2016–2019. Their presence is conclusively excluded on 12% of days. March, April, and May have a higher measurement cadence and show laminations on 41% of days. Individual months show laminations on up to 50% of days. Our results suggest that laminations are not rare phenomena at Eureka. To determine laminations’ likely contribution to Arctic weather and climate, local weather reports were obtained from the nearby Environment and Climate Change Canada (ECCC) weather station. Days with laminated clouds are strongly correlated with precipitating snow (r = 0.63), while days with non-laminated clouds (r = −0.40) and clear sky days (r = −0.43) are moderately anti-correlated with snow precipitation.

Decadal climate predictions with the Canadian Earth System Model version 5 (CanESM5)

Abstract. The Canadian Earth System Model version 5 (CanESM5) developed at Environment and Climate Change Canada's Canadian Centre for Climate Modelling and Analysis (CCCma) is participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). A 40-member ensemble of CanESM5 retrospective decadal forecasts (or hindcasts) is integrated for 10 years from realistic initial states once a year during 1961 to the present using prescribed external forcing. The results are part of CCCma's contribution to the Decadal Climate Prediction Project (DCPP) component of CMIP6. This paper evaluates CanESM5 large ensemble decadal hindcasts against observational benchmarks and against historical climate simulations initialized from pre-industrial control run states. The focus is on the evaluation of the potential predictability and actual skill of annual and multi-year averages of key oceanic and atmospheric fields at regional and global scales. The impact of initialization on prediction skill is quantified from the hindcasts decomposition into uninitialized and initialized components. The dependence of potential and actual skill on ensemble size is examined. CanESM5 decadal hindcasts skillfully predict upper-ocean states and surface climate with a significant impact from initialization that depend on climate variable, forecast range, and geographic location. Deficiencies in the skill of North Atlantic surface climate are identified and potential causes discussed. The inclusion of biogeochemical modules in CanESM5 enables the prediction of carbon cycle variables which are shown to be potentially skillful on decadal timescales, with a strong long-lasting impact from initialization on skill in the ocean and a moderate short-lived impact on land.

Continuing Persistence and Biomagnification of DDT and Metabolites in Northern Temperate Fruit Orchard Avian Food Chains

Dichlorodiphenyldichlorethane (1,1,1‐trichloro‐2,2‐bis(p‐chlorophenyl)ethane) (DDT) is an organochlorine insecticide that was widely used from the late 1940s to the 1970s in fruit orchards in the Okanagan valley, British Columbia, Canada, and in the process, contaminated American robin (Turdus migratorius) food chains with the parent compound and metabolite dichlorodiphenyldichloroethylene (1,1‐dichloro‐2,2‐bis(4‐chlorophenyl)ethylene) (p,p′‐DDE). In the present study, we examined the biological fate of these DDT‐related (DDT‐r) compounds at the same sites/region 26 years after a previous study by: (1) collecting soil, earthworms, and American robin eggs from apple, cherry, and pear orchards; (2) characterizing the diet and trophic positions of our biota using stable isotope analyses of δ13C and δ15N; and (3) estimating fugacity, biota‐soil‐accumulation factors (BSAFs), and biomagnification factors (BMFs). Mean p,p′‐DDE concentrations (soil: 16.1 µg/g organic carbon‐lipid equivalent; earthworms: 96.5 µg/g lipid equivalent; eggs: 568 µg/g lipid equivalent) revealed that contamination is present at elevated levels similar to the 1990s and our average soil DDE:DDT ratio of 1.42 confirmed that DDT is slowly degrading. American robins appeared to feed at similar trophic levels, but on different earthworms as indicated by egg stable isotope values (mean δ15N = 8.51‰ ± 0.25; δ13C = −26.32‰ ± 0.12). Lumbricidae and Aporrectodea worms shared a roughly similar δ15N value; however, Lumbricus terrestris showed a markedly enriched δ13C isotope, suggesting differences in organic matter consumption and physiological bioavailability. Biota‐soil‐accumulation factors and BMFs ranged over several orders of magnitude and were generally >1 and our fugacity analyses suggested that p,p′‐DDE is still thermodynamically biomagnifying in American robin food chains. Our results demonstrate that DDT‐r in fruit orchards remains bioavailable to free‐living terrestrial passerines and may pose a potential toxicological risk. Environ Toxicol Chem 2021;40:3379–3391. © 2021 Her Majesty the Queen in Right of Canada. 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.

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

Abstract The all-sky assimilation of radiances from microwave instruments is developed in the 4D-EnVar analysis system at Environment and Climate Change Canada (ECCC). Assimilation of cloud-affected radiances from Advanced Microwave Sounding Unit-A (AMSU-A) temperature sounding channels 4 and 5 for non-precipitating scenes over the ocean surface is the focus of this study. Cloud-affected radiances are discarded in the ECCC operational data assimilation system due to the limitations of forecast model physics, radiative transfer models, and the strong nonlinearity of the observation operator. In addition to using symmetric estimate of innovation standard deviation for quality control, a state-dependent observation error inflation is employed at the analysis stage. The background-state clouds are scaled by a factor of 0.5 to compensate for a systematic overestimation by the forecast model before being used in the observation operator. The changes in the fit of the background state to observations show mixed results. The number of AMSU-A channels 4 and 5 assimilated observations in the all-sky experiment is 5%–12% higher than in the operational system. The all-sky approach improves temperature analysis when verified against ECMWF operational analysis in the areas where the extra cloud-affected observations were assimilated. Statistically significant reductions in error standard deviation by 1%–4% for the analysis and forecasts of temperature, specific humidity, and horizontal wind speed up to maximum 4 days were achieved in the all-sky experiment in the lower troposphere. These improvements result mainly from the use of cloud information for computing the observation-minus-background departures. The operational implementation of all-sky assimilation is planned for the fall of 2021.

Bluebirds Experience Impaired Hatching Success in Conventionally Sprayed Apple Orchard Habitats: A 31-Year Study.

We analyzed the reproductive success of eastern bluebirds (Sialia sialis) nesting in apple orchards and non‐orchard nest‐boxes in southern Ontario, Canada, from 1988 to 2018. Using data from 2397 nest‐boxes monitored at 20 orchard sites and 52 non‐orchard sites, we first modeled phenological parameters typically linked to climate change across both site types. We found that the first egg of each brood was laid significantly earlier in the season each year over our 31‐year study. Clutch initiation occurred 4 days earlier in the spring in 2018 compared to 1988. Average clutch size in the first or second brood did not change significantly during our 31‐year study; however, clutches were significantly smaller in orchards compared to non‐orchards (0.10 ± 0.03 fewer eggs between sites). Nests built in orchards were also at 6.1‐fold greater risk of parasitism and 2.1‐fold greater risk of depredation than nests in non‐orchards. After accounting for depredation and nest parasitism, hatching success was still significantly lower in orchards than in non‐orchards. Overall, hatching success was 4%–5% lower in orchards. The probability of successfully fledging did not differ significantly between site types. In 2012, a ban on use of the organophosphate insecticide azinphos‐methyl in orchards was enacted in Canada. We did not find a difference in hatching or fledging success in orchards after the ban. In our assessment of available data, we conclude that any pesticide effect on hatching success of eastern bluebirds in sprayed orchards is most likely the consequence of long‐term exposure to dichlorodiphenyltrichloroethane (DDT) compounds in orchard soils and bioaccumulation in eggs rather than pesticides in use since regulation of DDT in the 1970s. Environ Toxicol Chem 2021;40:3369–3378. © 2021 Her Majesty the Queen in Right of Canada. 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.

Effects of quality controlled measured and re-analysed meteorological data on the performance of water temperature simulations

One of the most prominent sources of error and uncertainty in water quality modeling results is the input data. In this study, data from three meteorological databases were used to test the performance of a water temperature model of Lake Diefenbaker: the data from the Environment and Climate Change Canada (ECCC) had long-term quality control history (>20 years); the data from the AccuWeather had short-term quality control history (<10 years), and the data from the MeteoBlue database were modeled values. The CE-QUAL-W2 hydrodynamic and water quality model was used for this study. The models were calibrated by adjusting model coefficients controlling the amount of measured solar radiation and wind that reach the surface of the water. The sensitivity results showed very similar performances with slightly better performances (root mean square root difference of ±0.1) with the ECCC data followed by the MeteoBlue data and thereafter by the AccuWeather data respectively.

Air Quality Data Approach for Defining Wildfire Influence: Impacts on PM2.5, NO2, CO, and O3 in Western Canadian Cities

As the climate warms, it is recognized that wildfires are increasing in size and frequency. The negative effects of wildfires on air quality are well documented, especially on commonly monitored atmospheric pollutants such as PM2.5, NO2, CO, and O3. However, it is not clear how frequently wildfires influence urban air quality and the size of that influence relative to traffic and industrial pollutants. To understand the impact of wildfires on air quality, we have established an automated method to identify wildfire-influenced ambient air measurements. The trajectory-fire interception method (TFIM) compares hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) back-trajectories from an air quality monitoring station to satellite imagery of fire "hot-spots" to determine the number of trajectory-fire interceptions that occur. From the number of interceptions and local PM2.5 measurements, we have defined a wildfire-influenced period to occur if the interception count is ≥20. TFIM wildfire identification compares favorably with Environment and Climate Change Canada's smoke forecast, FireWork, and with the BlueSky trajectory-based forecast. Using TFIM, we studied the impact of wildfire-influenced periods on PM2.5, NO2, CO, and O3 from 2001 to 2019 in Western Canadian urban areas. We show that wildfire-influenced periods have elevated concentrations of PM2.5, NO2, and CO but not O3. We show that a decreasing urban baseline of CO and NO2 over time results in a relatively greater impact of wildfires on these pollutants, which emphasizes the changing relative importance of wildfires on air quality.