Nowcasting industrial production using linear and non-linear models of electricity demand

This article proposes different modelling approaches which exploit electricity market data to nowcast industrial production. Our models include linear, mixed-data sampling (MIDAS), Markov-Switching (MS) and MS-MIDAS regressions. Comparisons against autoregressive approaches and other commonly used macroeconomic predictors show that electricity market data combined with an MS model significantly improve nowcasting performance, especially during turbulent economic states, such as those generated by the recent COVID-19 pandemic. The most promising results are provided by an MS model which identifies two volatility regimes. These results confirm that electricity market data provide timely and easy-to-access information for nowcasting macroeconomic variables, especially when it is most valuable, i.e. during times of crisis and uncertainty

Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data

This is the final version. Available from Springer via the DOI in this record. In response to the COVID-19 emergency, many countries have introduced a series of social-distancing measures including lockdowns and businesses’ shutdowns, in an attempt to curb the spread of the infection. Accordingly, the pandemic has been generating unprecedented disruption on practically every aspect of society. This paper demonstrates that high-frequency electricity market data can be used to estimate the causal, short-run impacts of COVID-19 on the economy, providing information that is essential for shaping future lockdown policy. Unlike official statistics, which are published with a delay of a few months, our approach permits almost real-time monitoring of the economic impact of the containment policies and the financial stimuli introduced to address the crisis. We illustrate our methodology using daily data for the Italian day-ahead power market. We estimate that the 3 weeks of most severe lockdown reduced the corresponding Italian Gross Domestic Product (GDP) by roughly 30%. Such negative impacts are now progressively declining but, at the end of June 2020, GDP is still about 8.5% lower than it would have been without the outbreak.Università degli Studi di Trent

Large changes in Great Britain’s vegetation and agricultural land-use predicted under unmitigated climate change

This is the author accepted manuscript. The final version is available from IOP Publishing via the DOI in this recordData availability: The parameter values used for JULES is available from the suite u-ao645 and branch ‘full_UK’ on the Rosie repository: https://code.metoffice.gov.uk/trac/roses-u (registration required). The data that support the findings of this study are openly available at DOI.The impact of climate change on vegetation including agricultural production has been the focus of many studies. Climate change is expected to have heterogeneous effects across locations globally, and the diversity of land uses characterising Great Britain (GB) presents a unique opportunity to test methods for assessing climate change effects and impacts. GB is a relatively cool and damp country, hence, the warmer and generally drier growing season conditions projected for the future are expected to increase arable production. Here we use state-of-the-art, kilometre-scale climate change scenarios to drive a land surface model (JULES; Joint UK Land Environment Simulator) and an ECOnometric AGricultural land use model (ECO-AG). Under unmitigated climate change, by the end of the century, the growing season in GB is projected to get >5°C warmer and 140 mm drier on average. Rising levels of atmospheric CO2 are predicted to counteract the generally negative impacts of climate change on vegetation productivity in JULES. Given sufficient precipitation, warming favours higher value arable production over grassland agriculture, causing a predicted westward expansion of arable farming in ECO-AG. However, drying in the East and Southeast, without any CO2 fertilisation effect, is severe enough to cause a predicted reversion from arable to grassland farming. Irrigation, if implemented, could maintain this land in arable production. However, the predicted irrigation demand of ~200 mm (per growing season) in many locations is comparable to annual predicted runoff, potentially demanding large-scale redistribution of water between seasons and/or across the country. The strength of the CO2 fertilisation effect emerges as a crucial uncertainty in projecting the impact of climate change on GB vegetation, especially farming land-use decisions.Natural Environment Research Council (NERC)Joint UK BEIS/Defra Met Office Hadley Centre Climate Programm

The environmental impact of climate change adaptation on land use and water quality

Encouraging adaptation is an essential aspect of the policy response to climate change1. Adaptation seeks to reduce the harmful consequences and harness any beneficial opportunities arising from the changing climate. However, given that human activities are the main cause of environmental transformations worldwide2, it follows that adaptation itself also has the potential to generate further pressures, creating new threats for both local and global ecosystems. From this perspective, policies designed to encourage adaptation may conflict with regulation aimed at preserving or enhancing environmental quality. This aspect of adaptation has received relatively little consideration in either policy design or academic debate. To highlight this issue, we analyse the trade-offs between two fundamental ecosystem services that will be impacted by climate change: provisioning services derived from agriculture and regulating services in the form of freshwater quality. Results indicate that climate adaptation in the farming sector will generate fundamental changes in river water quality. In some areas, policies that encourage adaptation are expected to be in conflict with existing regulations aimed at improving freshwater ecosystems. These findings illustrate the importance of anticipating the wider impacts of human adaptation to climate change when designing environmental policies

The natural capital approach to integrating science, economics and policy into decisions affecting the natural environment

This is the final version. Available on open access from Cambridge University Press via the DOI in this recordNatural capital refers to those stocks of assets provided for free by nature which, directly or indirectly, deliver well-being for humans. These include freshwater, fertile soils, clean air and living things. Natural capital stocks deliver flows of services, often called ecosystem services, which (often in combination with flows from other capital including human labour, ingenuity and manufactured goods) produce the benefits upon which humans depend for economic well-being and their very existence. Economic activity depends on natural capital while also affecting the stock of those assets. This relationship between the environment, the economy and human well-being has caught the attention of governments at both global and national levels. But how should governments incorporate the notion of natural capital into policy- and decision-making? We set out to define the notion of natural capital and how it can be brought into the economic analyses which underpin the majority of policy decision-making systems. We consider the means by which changes can be best directed to reflect the underlying science of the environment, the incentives of the economy and the preferences of society.Natural Environment Research Council (NERC

Shifts in national land use and food production in Great Britain after a climate tipping point

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData availability: The modelled output data that support the findings of this study are openly available from: Smith, G. S. & Ritchie, P. D. L. (NERC Environmental Information Data Centre: 639 doi.org/10.5285/e1c1dbcf-2f37-429b-af19-a730f98600f6, 2019).Climate change is expected to impact agricultural land use. Steadily accumulating changes in temperature and water availability can alter the relative profitability of different farming activities and promote land use changes. There is also potential for high-impact ‘climate tipping points’ where abrupt, non-linear change in climate occurs - such as the potential collapse of the Atlantic Meridional Overturning Circulation (AMOC). Here, using data from Great Britain, we develop a methodology to analyse the impacts of a climate tipping point on land use and economic outcomes for agriculture. We show that economic/land use impacts of such a tipping point are likely to include widespread cessation of arable farming with losses of agricultural output, an order of magnitude larger than the impacts of climate change without an AMOC collapse. The agricultural effects of AMOC collapse could be ameliorated by technological adaptations such as widespread irrigation, but the amount of water required and the costs appear prohibitive in this instance.Natural Environment Research Council (NERC)Alan Turing Institut

The potential for land sparing to offset greenhouse gas emissions from agriculture

Greenhouse gas emissions from global agriculture are increasing at around 1% per annum, yet substantial cuts in emissions are needed across all sectors. The challenge of reducing agricultural emissions is particularly acute, because the reductions achievable by changing farming practices are limited and are hampered by rapidly rising food demand. Here we assess the technical mitigation potential offered by land sparing-increasing agricultural yields, reducing farm land area and actively restoring natural habitats on the land spared. Restored habitats can sequester carbon and can offset emissions from agriculture. Using the United Kingdom as an example, we estimate net emissions in 2050 under a range of future agricultural scenarios. We find that a land-sparing strategy has the technical potential to achieve significant reductions in net emissions from agriculture and land-use change. Coupling land sparing with demand-side strategies to reduce meat consumption and food waste can further increase the technical mitigation potential, however economic and implementation considerations might limit the degree to which this technical potential could be realised in practice.This research was funded by the Cambridge Conservation Initiative Collaborative Fund for Conservation and we thank its major sponsor Arcadia. We thank J. Bruinsma for the provision of demand data, the CEH for the provision of soil data and J. Spencer for invaluable discussions. A.L. was supported by a Gates Cambridge Scholarship.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nclimate291

Linking Land and Sea Through an Ecological-Economic Model of Coral Reef Recreation

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordCoastal zones are popular recreational areas that substantially contribute to social welfare. Managers can use information about specific environmental features that people value, and how these might change under different management scenarios, to spatially target actions to areas of high current or potential value. We explored how snorkelers' experience would be affected by separate and combined land and marine management actions in West Maui, Hawaiʻi, using a Bayesian belief network (BBN) and a spatially explicit ecosystem services model. The BBN simulates the attractiveness of a site for recreation by combining snorkeler preferences for coastal features with expert opinions on ecological dynamics, snorkeler behavior, and management actions. A choice experiment with snorkelers elucidated their preferences for sites with better ecological and water-quality conditions. Linking the economic elicitation to the spatially explicit BBN to evaluate land-sea management scenarios provides specific guidance on where and how to act in West Maui to maximize ecosystem service returns. Improving coastal water quality through sediment runoff and cesspool effluent reductions (land management), and enhancing coral reef ecosystem conditions (marine management) positively affected overall snorkeling attractiveness across the study area, but with differential results at specific sites. The highest improvements were attained through joint land-sea management, driven by strong efforts to increase fish abundance and reduce sediment; however, the effects of management at individual beaches varied.Pacific Islands Climate Science Center (PICSC)US Department of Agriculture National Institute of Food and Agriculture (USDA-NIFA)National Oceanic and Atmospheric Administration Coral Reef Conservation ProgramNational Socio-Environmental Synthesis Center (SESYNC

The potential of metering roundabouts: influence in transportation externalities

Roundabouts are increasingly being used on busy arterial streets for traffic calming purposes. However, if one roundabout leg is near a distribution hub, e.g. parking areas of shopping centers, the entry traffic volumes will be particularly high in peak hours. This paper investigated a partial-metering based strategy to reduce traffic-related costs in a corridor. Specifically, the resulting traffic performance, energy, environmental and exposure impacts associated with access roundabouts were studied in an urban commercial area, namely: a) to characterize corridor operations in terms of link-specific travel time, fuel consumption, carbon dioxide and nitrogen oxides emissions, and noise costs; b) to propose an optimization model to minimize above outputs; and c) to demonstrate the model applicability under different traffic demand and directional splits combinations. Traffic, noise and vehicle dynamics data were collected from a corridor with roundabouts and signalized intersections near a commercial area of Guimarães, Portugal. Microscopic traffic and emission modeling platforms were used to model traffic operations and estimate pollutant emissions, respectively. Traffic noise was estimated with a semi-dynamical model. Link-based cost functions were developed based on the integrated modeling structure. Lastly, a Sequential quadratic programming type approach was applied to find optimal timing settings. The benefit of the partial-metering system, in terms of costs, could be up to 13% with observed traffic volumes. The efficiency of the proposed system increased as entering traffic at the metered approaches increased (~7% less costs). The findings let one to quantify metering benefits near shopping areas