Physics-Informed Deep Learning to Reduce the Bias in Joint Prediction of Nitrogen Oxides

Atmospheric nitrogen oxides (NOx) primarily from fuel combustion have recognized acute and chronic health and environmental effects. Machine learning (ML) methods have significantly enhanced our capacity to predict NOx concentrations at ground-level with high spatiotemporal resolution but may suffer from high estimation bias since they lack physical and chemical knowledge about air pollution dynamics. Chemical transport models (CTMs) leverage this knowledge; however, accurate predictions of ground-level concentrations typically necessitate extensive post-calibration. Here, we present a physics-informed deep learning framework that encodes advection-diffusion mechanisms and fluid dynamics constraints to jointly predict NO2 and NOx and reduce ML model bias by 21-42%. Our approach captures fine-scale transport of NO2 and NOx, generates robust spatial extrapolation, and provides explicit uncertainty estimation. The framework fuses knowledge-driven physicochemical principles of CTMs with the predictive power of ML for air quality exposure, health, and policy applications. Our approach offers significant improvements over purely data-driven ML methods and has unprecedented bias reduction in joint NO2 and NOx prediction

Scaling Success: Lessons from Adaptation Pilots in the Rainfed Regions of India

"Scaling Success" examines how agricultural communities are adapting to the challenges posed by climate change through the lens of India's rainfed agriculture regions. Rainfed agriculture currently occupies 58 percent of India's cultivated land and accounts for up to 40 percent of its total food production. However, these regions face potential production losses of more than $200 billion USD in rice, wheat, and maize by 2050 due to the effects of climate change. Unless action is taken soon at a large scale, farmers will see sharp decreases in revenue and yields.Rainfed regions across the globe have been an important focus for the first generation of adaptation projects, but to date, few have achieved a scale that can be truly transformational. Drawing on lessons learnt from 21 case studies of rainfed agriculture interventions, the report provides guidance on how to design, fund and support adaptation projects that can achieve scale

The influence of long term trends in pollutant emissions on deposition of sulphur and nitrogen and exceedance of critical loads in the United Kingdom

In the United Kingdom, as with other European countries, land-based emissions of NOX and SO2 have fallen significantly over the last few decades. SO2 emissions fell from a peak of 3185 Gg S in 1970 to 344 Gg S in 2005 and are forecast by business-as-usual emissions scenarios to fall to 172 Gg by 2020. NOX emissions were at a maximum of 951 Gg N in 1970 and fell to 378 by 2005 with a further decrease to 243 Gg N forecast by 2020. These large changes in emissions have not been matched by emissions changes for NH3 which decreased from 315 Gg N in 1990 to 259 in 2005 and are forecast to fall to 222 by 2020. The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) has been applied to model the spatial distribution of sulphur and nitrogen deposition over the United Kingdom during a 15 year time period (1990-2005) and compared with measured deposition of sulphate, nitrate and ammonium from the national monitoring network. Wet deposition of nitrogen and sulphur was found to decrease more slowly than the emissions reductions rate. This is attributed to a number of factors including increases in emissions from international shipping and changing rates of atmospheric oxidation. The modelled time series was extended to a 50 year period from 1970 to 2020. The modelled deposition of SOx, NOy and NHx to the UK was found to fall by 87%, 52% and 25% during this period. The percentage of the United Kingdom surface area for which critical loads are exceeded is estimated to fall from 85% in 1970 to 37% in 2020 for acidic deposition and from 73% to 49% for nutrient nitrogen deposition. The significant reduction in land emissions of SO2 and NOX focuses further attention in controlling emissions from international shipping. Future policies to control emissions of ammonia from agriculture will be required to effect further significant reductions in nitrogen deposition

Occupant behaviour in naturally ventilated and hybrid buildings

Adaptive thermal comfort criteria for building occupants are now becoming established. In this paper we illustrate their use in the prediction of occupant behaviour and make a comparison with a non-adaptive temperature threshold approach. A thermal comfort driven adaptive behavioural model for window opening is described and its use within dynamic simulation illustrated for a number of building types. Further development of the adaptive behavioural model is suggested including use of windows, doors, ceiling fans, night cooling, air conditioning and heating, also the setting of opportunities and constraints appropriate to a particular situation. The integration in dynamic simulation of the thermal adaptive behaviours together with non-thermally driven behaviours such as occupancy, lights and blind use is proposed in order to create a more complete model of occupant behaviour. It is further proposed that this behavioural model is implemented in a methodology that includes other uncertainties (e.g. in internal gains) so that a realistic range of occupant behaviours is represented at the design stage to assist in the design of robust, comfortable and low energy buildings

Realigning the manufacturing priorities of SMEs as a result of the 2008 UK economic downturn

This study provides consideration of the impact made by the uncertain business environment experienced in recent times in the UK on manufacturing priorities within its SME sector. This uncertainty centres on the economy’s volatility during the recessionary period from 2008 onwards. A consequence of this is a realignment of manufacturing priorities, initiated by senior management within in the sector, accounting for sectoral conditions and associated market response. The study is based on a mixed methods research strategy, comprising a survey of 104 UK-based manufacturing SMEs and 17 interviewees with senior employees from these participating organisations. The study contributes to existing knowledge by building upon existing theoretical constructs of manufacturing strategy, specific to the manufacturing sector, and establishing a realignment of associated priorities around cost, flexibility, delivery performance and quality

Laissez faire and the Clean Development Mechanism: determinants of project implementation in Indian states, 2003–2011

India is the world’s second-largest host of projects implemented under the Kyoto Protocol’s Clean Development Mechanism (CDM). There is, however, considerable variation in the distribution of CDM projects implemented across different Indian states. While a large body of the literature examines cross-national variation in the implementation of CDM projects, few studies have analyzed the determinants of sub-national variation in different national contexts. We theorize that given India’s laissez-faire approach to CDM project implementation the availability of profitable climate mitigation opportunities and the political stability are two factors that promote CDM project implementation. Using sub-national data collected from a variety of sources, we conduct systematic analysis that provides empirical support for a set of hypotheses regarding the effects of these variables on project implementation. First, we find that states with a lot of public electricity-generating capacity and industrial capital implement more CDM projects than other states. Additionally, project developers rarely propose CDM projects during election years as a result of high levels of political uncertainty associated with those years. Our findings show that India’s liberal approach prevents the central government from using the CDM to promote sustainable development in less developed states. In India and other host countries where coordinated national policies to maximize their gains from CDM projects is absent, there is a paucity of project implementation in states that need it the most