179 research outputs found
Can seasonal and interannual variation in landscape CO2 fluxes be detected by atmospheric observations of CO2 concentrations made at a tall tower?
The coupled numerical weather model WRF-SPA (Weather Research and Forecasting
model and Soil-Plant-Atmosphere model) has been used to investigate a 3 yr
time series of observed atmospheric CO<sub>2</sub> concentrations from a tall tower
in Scotland, UK. Ecosystem-specific tracers of net CO<sub>2</sub> uptake and net
CO<sub>2</sub> release were used to investigate the contributions to the tower signal
of key land covers within its footprint, and how contributions varied at
seasonal and interannual timescales. In addition, WRF-SPA simulated
atmospheric CO<sub>2</sub> concentrations were compared with two coarse global
inversion models, CarbonTrackerEurope and the National Oceanic and
Atmospheric Administration's CarbonTracker (CTE-CT). WRF-SPA realistically
modelled both seasonal (except post harvest) and daily cycles seen in
observed atmospheric CO<sub>2</sub> at the tall tower (<i>R</i><sup>2</sup> = 0.67,
rmse = 3.5 ppm, bias = 0.58 ppm). Atmospheric CO<sub>2</sub> concentrations
from the tall tower were well simulated by CTE-CT, but the inverse model
showed a poorer representation of diurnal variation and simulated a larger
bias from observations (up to 1.9 ppm) at seasonal timescales, compared to
the forward modelling of WRF-SPA. However, we have highlighted a consistent
post-harvest increase in the seasonal bias between WRF-SPA and observations.
Ecosystem-specific tracers of CO<sub>2</sub> exchange indicate that the increased
bias is potentially due to the representation of agricultural processes
within SPA and/or biases in land cover maps. The ecosystem-specific tracers
also indicate that the majority of seasonal variation in CO<sub>2</sub> uptake for
Scotland's dominant ecosystems (forests, cropland and managed grassland) is
detectable in observations within the footprint of the tall tower; however,
the amount of variation explained varies between years. The between years
variation in detectability of Scotland's ecosystems is potentially due to
seasonal and interannual variation in the simulated prevailing wind
direction. This result highlights the importance of accurately representing
atmospheric transport used within atmospheric inversion models used to
estimate terrestrial source/sink distribution and magnitude
Greenhouse gas emissions, inventories and validation
The emission of greenhouse gases has become a very high priority research and environmental policy issue due to their effects on global climate. The knowledge of changes in global atmospheric concentrations of greenhouse gases since the industrial revolution is well documented, and the global budgets are reasonably well known. However, even at this scale there are important uncertainties in the budgets, for example, in the case of methane while the main sources and sinks have been identified, temporal changes in the global average concentrations since the early 1990s are not understood. In the absence of a quantitative explanation with appropriate experimental support, it is clear that current knowledge of the causes of changes in the global methane budget is inadequate to predict the effect of changes in specific emission sectors.
In developing control strategies to reduce emissions it is necessary to validate national emissions and their spatial disaggregation. The methodology to underpin such a process is at an early stage of development and is not fully implemented in any country, even though target emission reductions have already been announced. Furthermore, the scale of the emission reductions is large (eg of 60% reductions by 2050 relative to 1990 baseline). There is therefore an urgent requirement for measurement based verification processes to support such challenging emission reductions.
In this paper we provide the background in greenhouse gas emissions globally and in the UK followed by examples of approaches to validate emissions at the UK scale and within the regions
Depression: why drugs and electricity are not the answer
The dominant view within mental health services and research suggests that feeling depressed is a kind of medical illness, partially caused by various biological deficits which are somehow corrected by physical interventions. This article critically appraises evidence for the effectiveness and value of antidepressant drugs and electroconvulsive therapy (ECT), the two principle physical treatments recommended for depression. It also describes the negative effects of these interventions and raises concerns about how they impact the brain. We propose an alternative understanding that recognises depression as an emotional and meaningful response to unwanted life events and circumstances. This perspective demands that we address the social conditions that make depression likely and suggests that a combination of politics and common sense needs to guide us in providing help for one another when we are suffering in this way. This alternative view is increasingly endorsed around the world, including by the United Nations, the World Health Organization and service users who have suffered negative consequences of physical treatments that modify brain functions in ways that are not well-understood
Messing about with the brain: a response to commentaries on 'Depression: why electricity and drugs are not the answer'
Designing withdrawal support services for antidepressant users: Patients’ views on existing services and what they really need
BACKGROUND: Public Health England has recommended that services be put in place to support people who choose to withdraw from antidepressants because of a current gap. This study aims to explore the views of members of online withdrawal peer-support groups about existing healthcare and what additional support is needed. METHODS: The administrators of 15 online support groups for people stopping antidepressants were asked to advertise an online survey to their members. The survey, which was online from May 2021 to April 2022, was completed by 1276 people from 49 countries. RESULTS: 71% of respondents found their doctors' advice unhelpful (57% 'very unhelpful') regarding stopping an antidepressant; the main reasons being 'Recommended a reduction rate that was too quick for me', 'Not familiar enough with withdrawal symptoms to advise me' and 'Suggested stopping antidepressants would not cause withdrawal symptoms'. One in three did not seek advice from their prescriber when deciding whether to withdraw, with the main reasons being 'I felt they would not be supportive' (58%) and 'I felt that they didn't have the expertise to help me' (51%). The most common prescriber responses to those who did seek advice was 'Suggested a quick withdrawal schedule' (56%) and 'Not supportive and offered no guidance' (27%). The most common discontinuation periods recommended by doctors were one month (23%) and two weeks (19%). A range of potential professional services were rated 'very useful', most frequently: 'Access to smaller doses (e.g. tapering strips, liquid, smaller dose tablets) to ensure gradual reduction' (88%) and 'A health professional providing a personalised, flexible reduction plan' (79%). LIMITATIONS: This was a convenience sample, which may have been biased towards people who took longer to withdraw, and experienced more withdrawal symptoms, than antidepressant users in general. Black and ethnic minority people, and people without access to the internet, were underrepresented. CONCLUSIONS: Most participants reported their prescribers were unable to help them safely stop antidepressants, compelling them to turn to online peer-support groups instead. Our findings indicate, in keeping with previous studies, that clinicians require upskilling in safe tapering of antidepressants, and that patients need specialised services to help them stop safely
Quantifying methane and nitrous oxide emissions from the UK and Ireland using a national-scale monitoring network
The UK is one of several countries around the world that has enacted legislation to reduce its greenhouse gas emissions. In this study, we present top-down emissions of methane (CH4) and nitrous oxide (N2O) for the UK and Ireland over the period August 2012 to August 2014. These emissions were inferred using measurements from a network of four sites around the two countries. We used a hierarchical Bayesian inverse framework to infer fluxes as well as a set of covariance parameters that describe uncertainties in the system. We inferred average UK total emissions of 2.09 (1.65–2.67) Tg yr−1 CH4 and 0.101 (0.068–0.150) Tg yr−1 N2O and found our derived UK estimates to be generally lower than the a priori emissions, which consisted primarily of anthropogenic sources and with a smaller contribution from natural sources. We used sectoral distributions from the UK National Atmospheric Emissions Inventory (NAEI) to determine whether these discrepancies can be attributed to specific source sectors. Because of the distinct distributions of the two dominant CH4 emissions sectors in the UK, agriculture and waste, we found that the inventory may be overestimated in agricultural CH4 emissions. We found that annual mean N2O emissions were consistent with both the prior and the anthropogenic inventory but we derived a significant seasonal cycle in emissions. This seasonality is likely due to seasonality in fertilizer application and in environmental drivers such as temperature and rainfall, which are not reflected in the annual resolution inventory. Through the hierarchical Bayesian inverse framework, we quantified uncertainty covariance parameters and emphasized their importance for high-resolution emissions estimation. We inferred average model errors of approximately 20 and 0.4 ppb and correlation timescales of 1.0 (0.72–1.43) and 2.6 (1.9–20 3.9) days for CH4 and N2O, respectively. These errors are a combination of transport model errors as well as errors due to unresolved emissions processes in the inventory. We found the largest CH4 errors at the Tacolneston station in eastern England, which may be due to sporadic emissions from landfills and offshore gas in the North Sea
The need for antidepressant withdrawal support services: Recommendations from 708 patients
Approximately half of the tens of millions of people currently taking antidepressants will experience withdrawal symptoms when they try to reduce or come off them. Nearly half of these describe their symptoms as severe in surveys. Many prescribing doctors seem ill-informed and unprepared to provide effective discontinuation advice and support, often misdiagnosing withdrawal as a relapse of depression or anxiety. 708 members of online support groups for people on antidepressants, from 31 countries, completed a sentence in an online survey: 'A public health service to help people come off antidepressants should include ................'. Two independent researchers categorised their responses into themes, and then reached consensus via discussion. Seven themes emerged: 'Prescriber Role', 'Information', 'Other Supports/Services', 'Strong Negative Feelings re Doctors/Services etc.', Informed Consent When Prescribed', 'Drug Companies' and: 'Public Health Campaign'. The most frequently mentioned requirements of the Prescriber Role were that prescribers be properly informed, provide small doses/liquid/tapering strips, develop a withdrawal plan and believe patients about their withdrawal experiences. The most frequently recommended other services were psychotherapy/counselling, support groups, patient led/informed services, nutrition advice, 24-hour crisis support and 'holistic/lifestyle' approaches. Many respondents were angry about how uninformed their doctors were and how they had been treated
A Functional Approach to Vertical Turbulent Transport of Scalars in the Atmospheric Surface Layer
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