Reconstructing historical forest fire risk in the non-satellite era using the improved forest fire danger index and long short-term memory deep learning-a case study in Sichuan Province,southwestern China

Historical forest fire risk databases are vital for evaluating the effectiveness of past forest management approaches,enhancing forest fire warnings and emergency response capabilities,and accurately budgeting potential carbon emissions resulting from fires.However,due to the unavailability of spatial information technology,such databases are extremely difficult to build reliably and completely in the non-satellite era.This study presented an improved forest fire risk reconstruction framework that integrates a deep learning-based time series prediction model and spatial interpolation to address the challenge in Sichuan Province,southwestern China.First,the forest fire danger index(FFDI)was improved by supplementing slope and aspect information.We compared the performances of three time series models,namely,the autoregressive integrated moving average(ARIMA),Prophet and long short-term memory(LSTM)in predicting the modified forest fire danger index(MFFDI).The bestperforming model was used to retrace the MFFDI of individual stations from 1941 to 1970.Following this,the Anusplin spatial interpolation method was used to map the distributions of the MFFDI at five-year intervals,which were then subjected to weighted overlay with the distance-to-river layer to generate forest fire risk maps for reconstructing the forest fire danger database.The results revealed LSTM as the most accurate in fitting and predicting the historical MFFDI,with a fitting determination coefficient(R^2)of 0.709,mean square error(MSE)of0.047,and validation R^2 and MSE of 0.508 and 0.11,respectively.Independent validation of the predicted forest fire risk maps indicated that 5 out of 7 historical forest fire events were located in forest fire-prone areas,which is higher than the results determined from the original FFDI(2 out of 7).This proves the effectiveness of the improved MFFDI and indicates a high level of reliability of the historical forest fire risk reconstruction method proposed in this study.

Development Prospects of Osmanthus fragrans Mixed Wine Based on Liquor and Spirits

As a plant resource, Osmanthus fragrans has both medicinal and edible effects. This paper reviews the active components and health-care functions of O. fragrans, and introduces the current research situation of O. fragrans mixed wine. In addition, combined with the development of new products of plant-based flower wine, it analyzes the development prospects of O. fragrans mixed wine based on liquor and spirits.

Inter-comparisons of VOC oxidation mechanisms based on box model:A focus on OH reactivity

Volatile organic compounds(VOCs)oxidation processes play a very important role in atmospheric chemistry,and the chemical reactions are expressed in various manners in chemical mechanisms.To gain an improved understanding of VOCs evolution during oxidation processes and evaluate the discrepancies of VOCs oxidation schemes among different mechanisms,we used the total VOC reactivity as a diagnostic and evaluated tool to explore the differences for six widely used chemical mechanisms.We compared the total VOC reactivity evolution under high-NO_(x)xconditions for several sets of precursors,including n-pentane,toluene,ethene,isoprene and a mixture of 57 Photochemical Assessment Monitoring Stations(PAMS)species in a 0-D photochemical box model.Inter-comparison of total VOC reactivity of individual precursor simulations showed discrepancies to different extent of the oxidation schemes among the studied mechanisms,which are mainly attributed to the different lumping approaches for organic species.The PAMS simulation showed smaller discrepancy than individual precursor cases in terms of total VOC reactivity.SAPRC07 and RACM2 performances are found to better match the MCM for simulation of total VOC reactivity.Evidences suggest that the performance in simulating secondary organic products,OH concentrations and NO_(x)concentrations are related to the OH reactivity discrepancies among various chemical mechanisms.Information in this study can be used in selection of chemical mechanisms to better model OH reactivity in different environments.The results in this study also provide directions to further improve the ability in modelling total VOC reactivity with the chemical mechanisms.