Scaling up research on family justice using large-scale administrative data: an invitation to the socio-legal community

This article outlines the value of administrative data for family justice research. Although socio-legal scholars have extended their research beyond purely theoretical or doctrinal analyses, studies using large-scale digital datasets remain few in number. As new opportunities arise to link large-scale administrative datasets across health, education, welfare and justice, it is vital that the community of family justice researchers and analysts are supported to deliver research based on entire service or family court populations. In this context, this article provides a definition of administrative data, before outlining the potential of single, linked or blended administrative data sets for family justice research. The remaining sections of the article speak to questions that are pertinent to this particular academic community, including the distinctive contribution of the socio-legal scholar to interdisciplinary teams and the place of data providers in collaborative research. Drawing on the sociological concept of ‘publics’, the final section considers the multiple interest groups whose social licence must be secured, when personal records are used to understand the relationship between law and family life

Maternal health, pregnancy and birth outcomes for women involved in care proceedings in Wales: a linked data study

Background: Under the Children Act 1989, local authorities in Wales, UK, can issue care proceedings if they are concerned about the welfare of a child, which can lead to removal of a child from parents. For mothers at risk of child removal, timely intervention during pregnancy may avert the need for this and improve maternal/fetal health; however, little is known about this specific population during the antenatal period. The study examined maternity characteristics of mothers whose infants were subject to care proceedings, with the aim of informing preventative interventions targeted at high risk mothers. Methods: Anonymised administrative data from Cafcass Cymru, who provide child-focused advice and support for family court proceedings in Wales, were linked to population-based maternity and health records held within the Secure Anonymised Information Linkage Databank. Linked data were available for 1111 birth mothers of infants involved in care proceedings between 2015 and 2018. Findings were benchmarked with reference to an age-deprivation-matched comparison group (n = 23,414), not subject to care proceedings but accessing maternity services during this period. Demographic characteristics, maternal health, reproductive history, interaction with midwifery services, and pregnancy and birth outcomes were examined. Descriptive and statistical tests of independence were used. Results: Half of the women in the cohort (49.4%) resided in the most deprived areas. They were more likely to be younger at entry to motherhood (63.5% <21 years-of-age compared to 42.7% in the comparison group), to have mental health (28.6% compared to 8.2%) and substance use issues (10.4% compared to 0.6%) and to smoke (62.7% compared to 24.8%) during pregnancy. The majority first engaged with maternity services within their first trimester of pregnancy (63.5% compared to 84.4%). Babies were more likely to be born preterm (14.2% compared to 6.7%) and, for full-term babies, to have low birthweights (8.0% compared to 2.8%). Conclusion: This novel linkage study highlights multiple vulnerabilities experienced by pregnant mothers who have experienced care proceedings concerning an infant. Policy and practice colleagues require a clearer picture of women’s needs if child protection and health services are to offer effective services which prevent the need for family court proceedings and infant removal

Two years of satellite-based carbon dioxide emission quantification at the world's largest coal-fired power plants

Carbon dioxide (CO2) emissions from combustion sources are uncertain in many places across the globe. Satellites have the ability to detect and quantify emissions from large CO2 point sources, including coal-fired power plants. In this study, we routinely made observations with the PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite imaging spectrometer and the Orbiting Carbon Observatory-3 (OCO-3) instrument aboard the International Space Station at over 30 coal-fired power plants between 2021 and 2022. CO2 plumes were detected in 50 % of the acquired PRISMA scenes, which is consistent with the combined influence of viewing parameters on detection (solar illumination and surface reflectance) and unknown factors (e.g., daily operational status). We compare satellite-derived emission rates to in situ stack emission observations and find average agreement to within 27 % for PRISMA and 30 % for OCO-3, although more observations are needed to robustly characterize the error. We highlight two examples of fusing PRISMA with OCO-2 and OCO-3 observations in South Africa and India. For India, we acquired PRISMA and OCO-3 observations on the same day and used the high-spatial-resolution capability of PRISMA (30 m spatial/pixel resolution) to partition relative contributions of two distinct emitting power plants to the net emission. Although an encouraging start, 2 years of observations from these satellites did not produce sufficient observations to estimate annual average emission rates within low (&lt;15 %) uncertainties. However, as the constellation of CO2-observing satellites is poised to significantly improve in the coming decade, this study offers an approach to leverage multiple observation platforms to better quantify and characterize uncertainty for large anthropogenic emission sources.</p

Quantifying the influence of agricultural fires in northwest India on urban air pollution in Delhi, India

Since at least the 1980s, many farmers in northwest India have switched to mechanized combine harvesting to boost efficiency. This harvesting technique leaves abundant crop residue on the fields, which farmers typically burn to prepare their fields for subsequent planting. A key question is to what extent the large quantity of smoke emitted by these fires contributes to the already severe pollution in Delhi and across other parts of the heavily populated Indo-Gangetic Plain located downwind of the fires. Using a combination of observed and modeled variables, including surface measurements of PM2.5, we quantify the magnitude of the influence of agricultural fire emissions on surface air pollution in Delhi. With surface measurements, we first derive the signal of regional PM2.5 enhancements (i.e. the pollution above an anthropogenic baseline) during each post-monsoon burning season for 2012–2016. We next use the Stochastic Time-Inverted Lagrangian Transport model (STILT) to simulate surface PM2.5 using five fire emission inventories. We reproduce up to 25% of the weekly variability in total observed PM2.5 using STILT. Depending on year and emission inventory, our method attributes 7.0%–78% of the maximum observed PM2.5 enhancements in Delhi to fires. The large range in these attribution estimates points to the uncertainties in fire emission parameterizations, especially in regions where thick smoke may interfere with hotspots of fire radiative power. Although our model can generally reproduce the largest PM2.5 enhancements in Delhi air quality for 1–3 consecutive days each fire season, it fails to capture many smaller daily enhancements, which we attribute to the challenge of detecting small fires in the satellite retrieval. By quantifying the influence of upwind agricultural fire emissions on Delhi air pollution, our work underscores the potential health benefits of changes in farming practices to reduce fires

Two years of satellite-based carbon dioxide emission quantification at the world's largest coal-fired power plants

Carbon dioxide (CO2) emissions from combustion sources are uncertain in many places across the globe. Satellites have the ability to detect and quantify emissions from large CO2 point sources, including coal-fired power plants. In this study, we routinely made observations with the PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite imaging spectrometer and the Orbiting Carbon Observatory-3 (OCO-3) instrument aboard the International Space Station at over 30 coal-fired power plants between 2021 and 2022. CO2 plumes were detected in 50 % of the acquired PRISMA scenes, which is consistent with the combined influence of viewing parameters on detection (solar illumination and surface reflectance) and unknown factors (e.g., daily operational status). We compare satellite-derived emission rates to in situ stack emission observations and find average agreement to within 27 % for PRISMA and 30 % for OCO-3, although more observations are needed to robustly characterize the error. We highlight two examples of fusing PRISMA with OCO-2 and OCO-3 observations in South Africa and India. For India, we acquired PRISMA and OCO-3 observations on the same day and used the high-spatial-resolution capability of PRISMA (30 m spatial/pixel resolution) to partition relative contributions of two distinct emitting power plants to the net emission. Although an encouraging start, 2 years of observations from these satellites did not produce sufficient observations to estimate annual average emission rates within low (&lt;15 %) uncertainties. However, as the constellation of CO2-observing satellites is poised to significantly improve in the coming decade, this study offers an approach to leverage multiple observation platforms to better quantify and characterize uncertainty for large anthropogenic emission sources.</p

How should performance in EBUS mediastinal staging in lung cancer be measured?

There has been a paradigm shift in mediastinal staging algorithms in non-small cell lung cancer over the last decade in the United Kingdom (UK). This has seen endoscopic nodal staging (predominantly endobronchial ultrasound, EBUS) almost replace surgical staging (predominantly mediastinoscopy) as the pathological staging procedure of first choic

Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane

[EN] We review the capability of current and scheduled satellite observations of atmospheric methane in the shortwave infrared (SWIR) to quantify methane emissions from the global scale down to point sources. We cover retrieval methods, precision and accuracy requirements, inverse and mass balance methods for inferring emissions, source detection thresholds, and observing system completeness. We classify satellite instruments as area flux mappers and point source imagers, with complementary attributes. Area flux mappers are high-precision (< 1 %) instruments with 0.1-10 km pixel size designed to quantify total methane emissions on regional to global scales. Point source imagers are fine-pixel (< 60 m) instruments designed to quantify individual point sources by imaging of the plumes. Current area flux mappers include GOSAT (2009-present), which provides a high-quality record for interpretation of long-term methane trends, and TROPOMI (2018-present), which provides global continuous daily mapping to quantify emissions on regional scales. These instruments already provide a powerful resource to quantify national methane emissions in support of the Paris Agreement. Current point source imagers include the GHGSat constellation and several hyperspectral and multispectral land imaging sensors (PRISMA, Sentinel-2, Landsat-8/9, WorldView-3), with detection thresholds in the 100-10 000 kg h(-1) range that enable monitoring of large point sources. Future area flux mappers, including MethaneSAT, GOSAT-GW, Sentinel-5, GeoCarb, and CO2M, will increase the capability to quantify emissions at high resolution, and the MERLIN lidar will improve observation of the Arctic. The averaging times required by area flux mappers to quantify regional emissions depend on pixel size, retrieval precision, observation density, fraction of successful retrievals, and return times in a way that varies with the spatial resolution desired. A similar interplay applies to point source imagers between detection threshold, spatial coverage, and return time, defining an observing system completeness. Expanding constellations of point source imagers including GHGSat and Carbon Mapper over the coming years will greatly improve observing system completeness for point sources through dense spatial coverage and frequent return times.This research has been supported by the Collaboratory to Advance Methane Science (CAMS) and the National Aeronautics and Space Administration, Earth Sciences Division (grant no. NNH20ZDA001N-CMS).Jacob, DJ.; Varon, DJ.; Cusworth, DH.; Dennision, PE.; Frankenberg, C.; Gautam, R.; Guanter-Palomar, LM.... (2022). Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane. ATMOSPHERIC CHEMISTRY AND PHYSICS. 14:9617-9646. https://doi.org/10.5194/acp-22-9617-2022961796461