Emission Scheme Research Articles

Optimal parameters of Monte Carlo ray tracing solver with line-by-line spectral database for radiation modeling in fire

Thermal radiation is an important heat transfer mechanism in fire, but its modeling has often been over-simplified due to computational expense. In this study, we assess whether the Monte Carlo ray tracing (MCRT) method using the line-by-line (LBL) spectral database can serve as a fast and accurate candidate for solving radiation in fire. Using a snapshot extracted from a previous well-resolved simulation of a small turbulent pool fire, the radiation field is solved using a recently developed MCRT-LBL solver with three varying parameters: the number of rays per computational cell, the energy emission scheme, and the resolution of the LBL database. The energy equation is subsequently solved for one time step to assess the propagation of statistical noise into the temperature field. The radiative absorption is well predicted even with only one ray emitted per cell. Adaptive emission, where more rays are emitted at locations with stronger volumetric radiative emission, converges faster than the standard approach, where the same number of rays are emitted from every cell, although the advantage of the former is only pronounced when a sufficiently large number of rays are emitted. The statistical noise is smoothed in the calculation of the radiative heat source because the radiative emission is always predicted accurately regardless of the solver’s parameters. Further damping is provided by the energy equation, yielding a temperature field with negligible noise. Coarsening the LBL database only marginally affects the accuracy of the results, but it reduces the memory required to store the data to less than 10% of that of the original database. Lastly, when soot dominates radiative emission, the statistical noise of the radiation source is further reduced. In conclusion, the study indicates reasonable feasibility for applying MCRT-LBL in fire modeling, and we will further demonstrate this possibility in future studies using larger fires.

Urban water resources management with energy constraint and carbon emission intensity under uncertainty: A dual objective optimization model

Water production, utilization and recycle in urban system associated with a large amount of energy consumption and carbon emission that has increasingly international attention under sustainable development goals. In this study, a comprehensive urban water resources system management model is proposed under water-energy-carbon nexus and multiple uncertainties. The water-energy-carbon nexus was reflected in the processes of water extraction, water production and sewage treatment, and two objectives of maximizing the system benefit and minimizing carbon emission is transformed into two linear programming problem through the dual-objective interval fractional programming. Considering the interaction among water supply/demand, pollutants discharge control, energy consumption and self-energy utilization, indirect carbon emission as the main constraints, the developed model is applied to a typical water and energy sources shortage area of Qingdao city in north China. Multiple scenarios related to energy consumption and carbon emission control are designed to search the relationship among energy consumption, carbon emission and water resources allocation schemes. The results indicated that water demand as the main driving factor of energy consumption and carbon emission in urban water system cannot be directly limited through water supply structure adjustment. Through introducing self-energy supply (sludge utilization) and energy consumption control, water resources allocation schemes and water supply structure would be changed to improve energy saving potential with an obvious decrease trend of carbon emission intensity from 0.7921 tCO2/MWh to 0.5544 tCO2/MWh. The model could effectively provide reasonable urban water system management strategies under different water allocation demands and carbon emission challenges scenarios and deal with multiple uncertainties in decision-making process.

Optimal integration of electricity supply chain and sustainable closed-loop supply chain

This study presents an innovative multi-objective robust mixed-integer linear model to integrate an original capacitated Electricity Supply Chain (ESC) and a Closed-Loop Supply Chain (CLSC). The multifaceted relationships between the three dimensions of sustainability, different Carbon Emission Schemes (CES), and robustness have been carefully examined considering the Decision Maker’s (DM’s) various risk preferences. Results demonstrate the direct effect of the selected CES on the network configuration. Under each CES, the total cost increases by increasing the conservatism of the DM. At lower carbon emission capacity, the Carbon Cap Policy (CCP) has lower emissions at the highest cost compared to other policies. However, the emission capacity does not affect the emission under the Carbon Tax Policy (CTP) and Carbon Cap and Trade Policy (CCTP) but increases the network cost in both policies. A conservative DM is willing to adopt CTP with lower cost and emission at a higher emission capacity. At any level of emission capacity, CCTP has a higher priority than CTP only for non-conservative carbon-sensitive DM. The higher the DM conservatism, the lower the carbon credits sold under the CCTP, and the higher the need to purchase credits. Contrary to the insignificant effect of CESs, increasing the DM’s conservatism improves the robustness.

Fine scale simulation of sea salt aerosol under strong wind: WRF sensitivity test on PBL schemes and LES under Typhoon Hagibis

Identifying which factors among the planetary boundary layer (PBL) scheme, grid resolution, and source or sink terms dominantly influence the sea salt aerosol (SSA) spatial distribution is necessary. The dependence of SSA transport on PBL processes was investigated using a numerical weather prediction (NWP) model with a grid scale of ∼143 m. Size-segregated SSA transport during Typhoon Hagibis, which made landfall in Japan in 2019, was simulated using the Weather Research and Forecasting (WRF) model. The PBL schemes of Yonsei University (YSU), scale-aware YSU (Shin and Hong, 2015's scheme, SH) and Mellor-Yamada Nakanishi-Niino (MYNN), and large-eddy simulation (LES) subjected to turbulence transition enhancement via a cell perturbation method were tested to evaluate the reproducibility of observed values of wind speed, surface pressure, relative humidity, and temperature at meteorology masts. The results showed that wind speed was most influenced by the selection of the PBL scheme and LES. The distance from the coastline, as determined by the wind direction during the most intense typhoon stage, was correlated with a decrease in the time averaged SSA concentration when the storm moved inland. Despite the simulated SSA emission scheme's high sensitivity to wind speed (nearly 3rd power), the near-surface average concentration was less sensitive to the PBL schemes and LES selection than wind speed. However, the maximum arrival of the SSA differed by ∼20 % during the most vigorous stage of the typhoon. Budget analysis of the SSA transport equation highlighted that the advection term and gravity settling were most dependent on the PBL schemes and LES. The impacts of both factors on SSA transport were not limited to near-surface tendencies but were in a broader range over the atmosphere, up to 1–2 km. These results indicated that the vertical structure of the SSA field over the boundary layer depended on the PBL schemes and LES, thereby modulating the inland arrival of the SSA.

Research on carbon emission quota allocation scheme under "Double Carbon" target: a case study of industrial sector in Henan Province.

To achieve China's "Double Carbon" target, overall carbon emissions should be effectively controlled, and carbon emission quota (CEQ) allocation is an important tool. This study develops carbon emission prediction, CEQ allocation, and scheme feasibility evaluation models based on the principles of fairness, efficiency, and economy. The purpose is to propose a suitable CEQ allocation scheme for the Industrial Sector in Henan Province (ISHP). The results show that (1) the allocation model combining the technique for order preference by similarity to ideal solution (TOPSIS) and the zero-sum gains DEA (ZSG-DEA) can trade off the fairness and efficiency principles. (2) The reallocation scheme has an environmental Gini coefficient of 0.393 (< 0.4), which maximizes efficiency while lowering the abatement costs by 126.268 billion yuan, making it an ideal scheme that considers multiple principles. (3) CEQ should be reduced in 7 subsectors of ISHP while increasing in 33 others. Carbon emissions from these 7 subsectors are high, and CEQ should be reduced in accordance with the fairness principle. Even if their abatement costs are high and CEQ rises according to the efficiency principle, the increase is much smaller than the decrease. The findings are useful for optimizing the CEQ allocation under the "Double Carbon" target.

Sensitivity study and comparative evaluation of WRF-Chem over Iran: Available and embedded dust emission schemes

In this study, a severe dust storm has been simulated using the WRF-Chem model to investigate the accuracy of different dust emission schemes in estimating dust concentration in Tehran, the capital of Iran. First, by comparing the results of the GOCART, AFWA, UOC-2001, UOC-2004, and UOC-2011 dust emission schemes in WRF-Chem model, it is observed that the GOCART and AFWA schemes have the best performance compared to the in-situ measurements. The GOCART scheme with a better prediction of the trend of the dust concentration profile, and the AFWA scheme with a better prediction of the dust concentration peak value, are selected as the preferred schemes for this region. In the following, by using a two-way nested grid and embedding a new computational code for calculating the dust emission into the numerical model, an attempt has been made to increase the accuracy of the numerical model, especially in Tehran. Compared to the base model, the new dust emission scheme has decreased the overestimation of peak dust concentrations from observations by 24.9% and has enhanced the correlation coefficient by 0.12. Finally, by focusing on identifying dust sources, it is observed that external sources, namely Iraq and eastern Syria dry lands, have a significant influence on dust emissions. It is shown that the amount of mineral dust originating from these areas on February 20 and 21 is 1.5–1.9 Mg/km2. Also, the total dust particles lifted from the entire computing domain and Iran are 95.1 and 1.3 Tg, respectively.

Direct observations of NOxemissions over the San Joaquin Valley using airborne flux measurements during RECAP-CA 2021 field campaign

Abstract. Nitrogen oxides (NOx) are principle components of air pollution and serve as important ozone precursors. As the San Joaquin Valley (SJV) experiences some of the worst air quality in the United States, reducing NOx emissions is a pressing need, yet quantifying current emissions is complicated due to a mixture of mobile and agriculture sources. We performed airborne eddy covariance flux measurements during the Re-Evaluating the Chemistry of Air Pollutants in California (RECAP-CA) field campaign in June 2021. Combining footprint calculations and land cover statistics, we disaggregate the observed fluxes into component fluxes characterized by three different land cover types. On average, we find emissions of 0.95 mg N m−2 h−1 over highways, 0.43 mg N m−2 h−1 over urban areas, and 0.30 mg N m−2 h−1 over croplands. The calculated NOx emissions using flux observations are utilized to evaluate anthropogenic emissions inventories and soil NOx emissions schemes. We show that two anthropogenic inventories for mobile sources, EMFAC (EMission FACtors) and FIVE (Fuel-based Inventory for Vehicle Emissions), yield strong agreement with emissions derived from measured fluxes over urban regions. Three soil NOx schemes, including the MEGAN v3 (Model of Emissions of Gases and Aerosols from Nature), BEIS v3.14 (Biogenic Emission Inventory System), and BDISNP (Berkeley–Dalhousie–Iowa Soil NO Parameterization), show substantial underestimates over the study domain. Compared to the cultivated soil NOx emissions derived from measured fluxes, MEGAN and BEIS are lower by more than 1 order of magnitude, and BDISNP is lower by a factor of 2.2. Despite the low bias, observed soil NOx emissions and BDISNP present a similar spatial pattern and temperature dependence. We conclude that soil NOx is a key feature of the NOx emissions in the SJV and that a biogeochemical-process-based model of these emissions is needed to simulate emissions for modeling air quality in the region.

Exploring the carbon inequality embodied in China’s interregional trade based on a human well-being equity perspective

China’s interregional trade leads to interregional carbon inequality and impacts the flow and distribution of interregional human well-being. Few studies have been conducted that construct human well-being from a multidimensional perspective and explore the inequality of carbon emissions in interregional trade based on a human well-being equity perspective. This study applies a multiregional input‒output (MRIO) model to analyze the flow of carbon emissions and human well-being and capital between regions, explores the carbon inequality embodied in interregional trade based on the regional environmental inequality (REI) index, and finally proposes a shared responsibility scheme for carbon emissions and policy implications based on a human well-being equity perspective. The results demonstrate that the transfer of carbon emissions and human well-being through regional trade is realized through consumption. Different transfer paths of carbon emissions and human well-being lead to significant carbon inequality in interregional trade. Regions such as the West and North, which suffer more significant inequality in trade, receive carbon emissions mainly from carbon-intensive industries; regions such as the East coast and South coast, which benefit more from trade, transfer large amounts of carbon emissions by importing products from industrial sectors with a high carbon emission intensity and relatively low value and by acquiring more human well-being and capital. This study provides evidence regarding the current status of carbon inequality based on human well-being equity in China; fills the gap in existing research; and provides a reference for addressing the inequality of carbon emissions and human well-being and each type of capital between regions and formulating a fair and effective carbon reduction policy. This study provides an overall solution for sustainable development in China.

All-Optical Electrochemiluminescence.

Electrochemiluminescence (ECL) is widely employed for medical diagnosis and imaging. Despite its remarkable analytical performances, the technique remains intrinsically limited by the essential need for an external power supply and electrical wires for electrode connections. Here, we report an electrically autonomous solution leading to a paradigm change by designing a fully integrated all-optical wireless monolithic photoelectrochemical device based on a nanostructured Si photovoltaic junction modified with catalytic coatings. Under illumination with light ranging from visible to near-infrared, photogenerated holes induce the oxidation of the ECL reagents and thus the emission of visible ECL photons. The blue ECL emission is easily viewed with naked eyes and recorded with a smartphone. A new light emission scheme is thus introduced where the ECL emission energy (2.82 eV) is higher than the excitation energy (1.18 eV) via an intermediate electrochemical process. In addition, the mapping of the photoelectrochemical activity by optical microscopy reveals the minority carrier interfacial transfer mechanism at the nanoscale. This breakthrough provides an all-optical strategy for generalizing ECL without the need for electrochemical setups, electrodes, wiring constraints, and specific electrochemical knowledge. This simplest ECL configuration reported so far opens new opportunities to develop imaging and wireless bioanalytical systems such as portable point-of-care sensing devices.

Positive Feedback of Dust Direct Radiative Effect on Dust Emission in Taklimakan Desert

AbstractDust direct radiative effect (DDRE) can modify the near‐surface air temperature, which can in turn influence dust emission. However, the feedback mechanism of DDRE on dust emission is poorly understood. In this study, the influence of DDRE on dust emission in Taklimakan Desert (TD) was investigated using comprehensive ground‐based observations. The results show that the near‐surface air temperature significantly decreased as a result of DDRE, corresponding to dust emission enhanced. Statistically, the contributions of DDRE to dust emission during light, moderate, and heavy dusty episodes were 5.0% (3.6%), 5.2% (2.8%), and 6.1% (3.3%) in spring (summer), respectively. From the perspective of mechanism, DDRE can induce an increase in air density by cooling the near‐surface, causing an enhancement of aerodynamic drag, promoting dust emission in TD. Such positive feedback of DDRE on dust emission may be a potential contributor to improving the dust emission scheme of numerical modeling in the future.

A new process-based and scale-aware desert dust emission scheme for global climate models – Part I: Description and evaluation against inverse modeling emissions

Abstract. Desert dust accounts for most of the atmosphere's aerosol burden by mass and produces numerous important impacts on the Earth system. However, current global climate models (GCMs) and land-surface models (LSMs) struggle to accurately represent key dust emission processes, in part because of inadequate representations of soil particle sizes that affect the dust emission threshold, surface roughness elements that absorb wind momentum, and boundary-layer characteristics that control wind fluctuations. Furthermore, because dust emission is driven by small-scale (∼ 1 km or smaller) processes, simulating the global cycle of desert dust in GCMs with coarse horizontal resolutions (∼ 100 km) presents a fundamental challenge. This representation problem is exacerbated by dust emission fluxes scaling nonlinearly with wind speed above a threshold wind speed that is sensitive to land-surface characteristics. Here, we address these fundamental problems underlying the simulation of dust emissions in GCMs and LSMs by developing improved descriptions of (1) the effect of soil texture on the dust emission threshold, (2) the effects of nonerodible roughness elements (both rocks and green vegetation) on the surface wind stress, and (3) the effects of boundary-layer turbulence on driving intermittent dust emissions. We then use the resulting revised dust emission parameterization to simulate global dust emissions in a standalone model forced by reanalysis meteorology and land-surface fields. We further propose (4) a simple methodology to rescale lower-resolution dust emission simulations to match the spatial variability of higher-resolution emission simulations in GCMs. The resulting dust emission simulation shows substantially improved agreement against regional dust emissions observationally constrained by inverse modeling. We thus find that our revised dust emission parameterization can substantially improve dust emission simulations in GCMs and LSMs.

Updated isoprene and terpene emission factors for the Interactive BVOC (iBVOC) emission scheme in the United Kingdom Earth System Model (UKESM1.0)

Abstract. Biogenic volatile organic compounds (BVOCs) influence atmospheric composition and climate, and their emissions are affected by changes in land use and land cover (LULC). Current Earth system models calculate BVOC emissions using parameterisations involving surface temperature, photosynthetic activity, CO2 and vegetation type and use emission factors (EFs) to represent the influence of vegetation on BVOC emissions. We present new EFs for the Interactive BVOC Emission Scheme (iBVOC) used in the United Kingdom Earth System Model (UKESM), based on those used by the Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1 scheme. Our new EFs provide an alternative to the current EFs used in iBVOC, which are derived from older versions of MEGAN and the Organizing Carbon and Hydrology in Dynamic Ecosystem (ORCHIDEE) emission scheme. We show that current EFs used by iBVOC result in an overestimation of isoprene emissions from grasses, particularly C4 grasses, due to an oversimplification that incorporates the EF of shrubs (high isoprene emitters) into the EF for C3 and C4 grasses (low isoprene emitters). The current approach in iBVOCs assumes that C4 grasses are responsible for 40 % of total simulated isoprene emissions in the present day, which is much higher than other estimates of ∼ 0.3 %–10 %. Our new isoprene EFs substantially reduce the amount of isoprene emitted by C4 grasslands, in line with observational studies and other modelling approaches, while also improving the emissions from other known sources, such as tropical broadleaf trees. Similar results are found from the change to the terpene EF. With the new EFs, total global isoprene and terpene emissions are within the range suggested by the literature. While the existing model biases in the isoprene column are slightly exacerbated with the new EFs, other drivers of this bias are also noted. The disaggregation of shrub and grass EFs provides a more faithful description of the contribution of different vegetation types to BVOC emissions, which is critical for understanding BVOC emissions in the pre-industrial and under different future LULC scenarios, such as those involving wide-scale reforestation or deforestation. Our work highlights the importance of using updated and accurate EFs to improve the representation of BVOC emissions in Earth system models and provides a foundation for further improvements in this area.

Data-driven aeolian dust emission scheme for climate modelling evaluated with EMAC 2.55.2

Abstract. Aeolian dust has significant impacts on climate, public health, infrastructure and ecosystems. Assessing dust concentrations and the impacts is challenging because the emissions depend on many environmental factors and can vary greatly with meteorological conditions. We present a data-driven aeolian dust scheme that combines machine learning components and physical equations to predict atmospheric dust concentrations and quantify the sources. The numerical scheme was trained to reproduce dust aerosol optical depth retrievals by the Infrared Atmospheric Sounding Interferometer on board the MetOp-A satellite. The input parameters included meteorological variables from the fifth-generation atmospheric reanalysis of the European Centre for Medium-Range Weather Forecasts. The trained dust scheme can be applied as an emission submodel to be used in climate and Earth system models, which is reproducibly derived from observational data so that a priori assumptions and manual parameter tuning can be largely avoided. We compared the trained emission submodel to a state-of-the-art emission parameterisation, showing that it substantially improves the representation of aeolian dust in the global atmospheric chemistry–climate model EMAC.

Dust emission and potential diffusion process in Mongolia

AbstractMongolian dust is an important part of Asian aerosols, which highly influences regional ecological balance and atmospheric environment cycling. Detailed and systematic research is essential for downwind countries of Mongolia to formulate appropriate strategies for dust disaster prevention. In this study, a size‐resolved dust emission scheme and a hybrid single‐particle Lagrangian integrated trajectory model were coupled to reproduce the Mongolian dust events. For the dust storm that occurred on March 14, 2021, the simulated dust source was mainly located in the Gobi Provinces and a narrow strip between the Altai and Khangai Mountains. The potential diffusion area of dust was approximately 8.59 × 106 km2. The long‐term simulation between 2001 and 2020 shows that Mongolian dust sources can be divided into three areas: southwest Mongolia, the Gobi Provinces, and the area between the Altai and Khangai Mountains. Dust emissions can reach 100.6 Tg year−1, affecting approximately 12.6 × 106 km2 of land in East Asia. The emission and transport characteristics of Mongolian dust vary according to the sources. Southwestern Mongolia has the most severe dust emissions and the Gobi Provinces have the strongest diffusion capacity. Southern Mongolia and northern China have always been the hotspots of Mongolian dust transportation and deposition and thus require more research attention. This study provides a comprehensive analysis of Mongolian dust and presents a potential diffusion map that can be used to formulate preventive measures.

Coase and Cap-and-Trade: Evidence on the Independence Property from the European Carbon Market

I examine the Coasean independence property in a large multinational cap-and-trade scheme for greenhouse gas emissions, the EU Emissions Trading System. I analyze whether emissions of power producers are independent from allowance allocations by leveraging a change in allocation policy for a difference-in-difference strategy. The evidence suggests that the independence property holds overall and for larger emitters and that firms respond to the loss in allocation by increasing allowance purchases. Suggestive evidence for small emitters indicates that trading costs or behavioral bias distorts their emission decisions. However, their small emission share leaves the independence property intact at the sector level. (JEL L94, L98, Q48, Q51, Q54, Q58)

Third Time’s a Charm? Assessing the Impact of the Third Phase of the EU ETS on CO2 Emissions and Performance

The EU Emissions Trading System (ETS) is the largest cap-and-trade scheme for CO2 emissions globally. This study evaluates the impact on CO2-equivalents emission of the increased stringency of Phase 3, which marked a significant shift from the previous phases of the EU ETS and significantly reduced the number of emissions permits (EU Allowances—EUA) freely allocated. Our analysis reveals that the increase of purchased EUA had a statistically significant, substantial impact on emissions reduction from Phase 2 to Phase 3, with a decrease in emissions of approximately half a ton for each additional allowance bought. Our (conservative) estimate of the total reduction in emission is 422 MtCO2-eq, 22.5% of the average yearly EU ETS emissions or 4.3–3.0% of emissions in Phases 2 and 3, respectively. Under Article 10c of the ETS directive, lower-income Member States have been allowed to continue the free allocation of EUA to electricity-generating installations during Phase 3 to provide more time and resources for modernization. We show that such derogation had a sizeable and significant detrimental impact on the achievement of emission reduction targets, leading to an increase in emissions of about half a ton for each additional allowance bought; a result that highlights the need for increased efforts on support measures (e.g., the Modernization Fund). We also investigate the impact of the EU ETS on output, capital productivity, and labour productivity. Our analysis indicates that the performances were not negatively impacted by the tightening in regulation that occurred between Phases 2 and 3. We also find no evidence that the derogation status impacted performances, which further ameliorates the concerns about the potential intra-EU competitive distortions induced by the regulation. Our results cast a favourable light on the reduction of the free allocation of EUA and the tightening of the regulation implemented in Phase 4 of the EU ETS.

Including ash in UKESM1 model simulations of the Raikoke volcanic eruption reveals improved agreement with observations

Abstract. In June 2019 the Raikoke volcano, located in the Kuril Islands northeast of the Japanese archipelago, erupted explosively and emitted approximately 1.5 Tg ± 0.2 Tg of SO2 and 0.4–1.8 Tg of ash into the upper troposphere and lower stratosphere. Volcanic ash is usually neglected in modelling stratospheric climate changes since larger particles have generally been considered to be short-lived particles in terms of their stratospheric lifetime. However, recent studies have shown that the coagulation of mixed particles with ash and sulfate is necessary to model the evolution of aerosol size distribution more accurately. We perform simulations using a nudged version of the UK Earth System Model (UKESM1) that includes a detailed two-moment aerosol microphysical scheme for modelling the oxidation of sulfur dioxide (SO2) to sulfate aerosol and the detailed evolution of aerosol microphysics in the stratosphere. We compare the model with a wide range of observational data. The current observational network, including satellites, surface-based lidars, and high-altitude sun photometers means that smaller-scale eruptions such as Raikoke provide unprecedented detail of the evolution of volcanic plumes and processes, but there are significant differences in the evolution of the plume detected using the various satellite retrievals. These differences stem from fundamental differences in detection methods between, e.g. lidar and limb-sounding measurement techniques and the associated differences in detection limits and the geographical areas where robust retrievals are possible. This study highlights that, despite the problems in developing robust and consistent observational constraints, the balance of evidence suggests that including ash in the model emission scheme provides a more accurate simulation of the evolution of the volcanic plume within UKESM1.

Improved Performance of CLM5.0 Model in Frozen Soil Simulation Over Tibetan Plateau by Implementing the Vegetation Emissivity and Gravel Hydrothermal Schemes

AbstractFrozen soil is widely distributed over the Tibetan Plateau (TP) and has significant impacts on the regional climate and ecosystem. However, the Community Land Model version 5 (CLM5.0) produces evident cold bias in the frozen soil simulation over TP. In this study, an improved vegetation emissivity scheme and a gravel hydrothermal scheme have been implemented into CLM5.0 model, and their synergistic influences on the frozen soil simulation over TP have been systematically addressed and revealed. Results show that adopting the vegetation emissivity scheme, the gravel hydrothermal scheme, and both can remarkably reduce the cold bias in the frozen soil simulated by the original CLM5.0 model, and the column mean root‐mean‐square error (RMSE) can be reduced by 12.88%, 20.68%, and 31.11% at Arou site and 25.03%, 10.15%, and 36.87% at Maqu site, respectively. The reductions of column mean RMSE for the modeled soil temperature regionally averaged over TP induced by the adoption of vegetation emissivity scheme, the gravel hydrothermal scheme, and both are 32.34%, 6.75%, and 30.18%, respectively. The underlying physical mechanisms are related to the improved representation of the soil hydrothermal processes above or in the soil. The improved vegetation emissivity scheme improves the soil surface long‐wave radiation heat transfer process, while the gravel hydrothermal scheme improves the hydrothermal properties within the soil. Overall, improving the surface long‐wave radiation heat transfer and the internal soil hydrothermal properties can obviously enhance the performance of CLM5.0 model in simulating the soil freeze–thaw processes.

An Urban Scheme for the ECMWF Integrated Forecasting System: Global Forecasts and Residential CO2 Emissions

AbstractThe impact of urbanization on local weather patterns affects over half the global population. Global numerical weather prediction systems have reached a resolution at which urban conurbations can be spatially resolved, justifying their representation within land surface parameterizations with the aim of improving local predictions. Additionally, real‐time atmospheric monitoring of trace gas emissions can utilize weather variables relevant for urban areas. We investigated whether a simple single‐layer urban canopy scheme can be used within a global forecast model to jointly improve predictions of near‐surface weather variables and residential CO2 emissions. The scheme has been implemented in the Integrated Forecast System used operationally at the European Centre for Medium‐Range Weather Forecasts running at ∼9 km horizontal resolution. First, we selected a suitable urban land cover map (ECOCLIMAP‐SG) based on comparisons with regional data and land surface temperature MODIS retrievals. The urban scheme is verified by providing improved 2 m temperature (∼10%) and 10 m wind (∼17%) RMSE values for both summer and winter months around urban environments. The influence of the scheme was most noticeable at night. Additionally, we have implemented a simple temperature‐dependent residential emissions model to calculate real‐time CO2 heating emissions. These were validated against existing offline products, national reporting and by comparing atmospheric simulations with total column CO2 observations. The results show an improved temporal variability of emissions, which arise from synoptic scale temperature changes. Given the improved predictability from the urban scheme for both weather and emissions, it will be operationally implemented in an upcoming model cycle.

Simulating the Transport and Rupture of Pollen in the Atmosphere

AbstractPollen, one type of primary biological aerosol particle (PBAP), is emitted from the terrestrial biosphere and can undergo physical changes in the atmosphere via particle rupture. To examine the fate of pollen and its atmospheric processing, a pollen emission and transport scheme is coupled to the Weather Research and Forecasting Model with Chemistry (WRF‐Chem). We simulate the emission of pollen and its impacts on the cloud properties and precipitation in the Southern Great Plains from 12 to 19 April 2013, a period with both high pollen emissions and convective activity. We conduct a suite of ensemble runs that simulate primary pollen and three different pollen rupture mechanisms that generate subpollen particles, including (a) high humidity‐induced surface rupture, (b) high humidity‐induced in‐atmosphere plus surface rupture, and (c) lightning‐induced rupture, where in‐cloud and cloud‐to‐ground lightning strikes trigger pollen rupture events. When relative humidity is high (&gt;80%), coarse primary pollen (∼1 μg m−3) is converted into fine subpollen particles (∼1.2e−4 μg m−3), which produces 80% more subpollen particles than lightning‐induced rupture. The in‐atmosphere humidity‐driven rupture predominantly produces subpollen particles, which is further enhanced during a frontal thunderstorm. During strong convection, vertical updrafts lift primary pollen and subpollen particles (∼0.5e−4 μg m−3) to the upper troposphere (∼12 km) and laterally transports the ruptured pollen in the anvil top outflow. In regions of high pollen and strong convection, ruptured pollen can influence warm cloud formation by decreasing low cloud (&lt;4 km) cloud water mixing ratios and increasing ice phase hydrometeors aloft (&gt;10 km).