Numerical Simulation of the Effect of Construction Dust Emission on Air Quality in Jinan, a Central City in the North China Plain

<p>Numerical simulation was conducted to assess the impact of dust emission on typical environmental sites in Jinan City. The CALPUFF model was applied to five simulation scenarios. The results showed that dust emission had a significant impact on air quality in Jinan. The impact of dust emission on the average concentration of PM10 at 15 monitoring sites was 19.8 μg/m3, accounting for 14.9% of the annual total. The impact of dust emission on the average concentration of PM2.5 was 5.2 μg/m3, accounting for 8.1% of the annual total. Adoption of yellow warning measures in the emission reduction scenarios had insignificant environmental effects due to unfavorable meteorological conditions. Compared with the baseline scenario, the average concentrations of PM10 and PM2.5 decreased by 13.6% and 1.9%, respectively. After adoption of orange and red warning measures, the impact of site dust emission on air quality at the monitoring site was reduced significantly. Significant environmental effects were achieved after all construction sites within a 2-km radius of the monitoring site were closed. Compared with the baseline scenario, the average concentrations of PM10 and PM2.5 were reduced by 45.5% and 42.3%, respectively. The results showed that under adverse meteorological conditions, higher-level warning measures should be undertaken to reduce the impact of site emissions on environmental quality. Considering the economic and social effects of emission reduction, temporary construction stoppage within 2 km of the monitoring site is a feasible plan that is in accordance with the goals of comprehensive environmental management.</p>

Integrated Water Balance and Water Quality Management Under Future Climate Change and Population Growth: A Case Study of Upper Litani Basin, Lebanon

The impacts of the growing population at Lebanon including Lebanese, Palestinian and Syrian refugees, associated with the changing climate parameters such that the precipitation are putting the Bekaa Valley’s water resources in a stymie situation. The water resources are under significant stress limiting the water availability and deteriorating the water quality at the Upper Litani River Basin (ULRB) within the Bekaa Valley region. These impacts are assessed by Water Evaluation And Planning model to assure the water balance and quality at baseline scenario in 2013, and future scenarios reaching 2095, serving by the Watershed Modeling System to get the flow throughout the Litani River’s ungauged zones. Moreover, a General Circulation Model is used to predict the future climate up to 2100 under several emissions scenarios which shows a critical situation at the high emission scenario where the precipitation will be reduced about 87 mm from 2013 to 2095. The aim of this research is to reduce the water pollution that limits the availability of usable water, and to minimize the gap between the demand and supply of water within the ULRB in order to maintain water resources sustainability, and preserves its quality, even after 80 years. In particular, this may be achieved by removing encroachments on the river, by adding waste water treatment plants, by reducing the amount of lost water in damaged water network, and by avoiding the overconsumption of groundwater.

Estimating the transmissibility of SARS-CoV-2 VOC 202012/01 in Japan using travel history information

<abstract> <p>Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has rapidly spread across the globe. The variant of concern (VOC) 202012/01 (B.1.1.7, also known as the alpha variant) bearing the N501Y mutation emerged in late 2020. VOC 202012/01 was more transmissible than existing SARS-CoV-2 variants and swiftly became dominant in many regions. More than 150 cases of VOC 202012/01 were reported in Japan by 26 February 2021. During the very early stage of introduction, only a subset arose from domestic transmission. If the reproduction number <italic>R</italic> (i.e., the average number of secondary transmission events caused by a single primary case) is greater than 1, the corresponding proportion should converge to 1 in a short period of time, and thus it is critical to understand the transmissibility of VOC 202012/01 based on travel history information. The present study aimed to estimate <italic>R</italic> of VOC 202012/01 using overseas travel history information. A mathematical model was developed to capture the relationship between travel history and <italic>R</italic>. We obtained travel history data for each confirmed case of VOC 202012/01 infection from 26 December 2020 to 26 February 2021. Maximum likelihood estimation was used to estimate <italic>R</italic>, accounting for right censoring during real-time estimation. In the baseline scenario, <italic>R</italic> was estimated at 2.11 (95% confidence interval: 1.63, 2.94). By 26 February 2021, an average of nine generations had elapsed since the first imported case. If the generation time of VOC 202012/01 was assumed to be longer, <italic>R</italic> was increased, consistent with estimates of <italic>R</italic> from case data. The estimated <italic>R</italic> of VOC 202012/01 in Japan exceeded 1 on 26 February 2021, suggesting that domestic transmission events caused a major epidemic. Moreover, because our estimate of <italic>R</italic> was dependent on generation time and ascertainment biases, continuous monitoring of contact tracing data is crucial to decipher the mechanisms of increased VOC 202012/01 transmissibility.</p> </abstract>

Using public participation within land use change scenarios for analysing environmental and socioeconomic drivers

This paper aims to improve the understanding of environmental and socioeconomic drivers on land use change (LUC) through public participation (PP), and provide recommendations for long-term policy making to support sustainable land use management. Public participation (PP) was necessary to help understand and address the problem and concerns of stakeholders within the study area. Through two collaboration workshops seven individual future land use scenarios were created. Using the FLUS (Future land use simulation) model, land use was projected up till 2060, after which logistic regression analysis took place to find the most significant driver. Results found that LUC within the baseline scenario and the ones chosen by stakeholders were very different, however concluded that Paddy field extent would decrease in the future to be replaced by more drought resilient agriculture; Perennials & Orchards and Field Crops. Outcomes from future scenarios propose that future LUC was driven by environment spatial factors such as elevation and climate, not soil suitability. With, first hand interviews suggesting it is indirect external factors such as, crop price that drive LUC. Overall the study provides steps towards dynamic LUC modelling where future scenarios have been tailored to details specified by the public through their participation.

Assimilation of Wheat and Soil States into the APSIM-Wheat Crop Model: A Case Study

Optimised farm crop productivity requires careful management in response to the spatial and temporal variability of yield. Accordingly, combination of crop simulation models and remote sensing data provides a pathway for providing the spatially variable information needed on current crop status and the expected yield. An ensemble Kalman filter (EnKF) data assimilation framework was developed to assimilate plant and soil observations into a prediction model to improve crop development and yield forecasting. Specifically, this study explored the performance of assimilating state observations into the APSIM-Wheat model using a dataset collected during the 2018/19 wheat season at a farm near Cora Lynn in Victoria, Australia. The assimilated state variables include (1) ground-based measurements of Leaf Area Index (LAI), soil moisture throughout the profile, biomass, and soil nitrate-nitrogen; and (2) remotely sensed observations of LAI and surface soil moisture. In a baseline scenario, an unconstrained (open-loop) simulation greatly underestimated the wheat grain with a relative difference (RD) of −38.3%, while the assimilation constrained simulations using ground-based LAI, ground-based biomass, and remotely sensed LAI were all found to improve the RD, reducing it to −32.7%, −9.4%, and −7.6%, respectively. Further improvements in yield estimation were found when: (1) wheat states were assimilated in phenological stages 4 and 5 (end of juvenile to flowering), (2) plot-specific remotely sensed LAI was used instead of the field average, and (3) wheat phenology was constrained by ground observations. Even when using parameters that were not accurately calibrated or measured, the assimilation of LAI and biomass still provided improved yield estimation over that from an open-loop simulation.

Using Decomposition Analysis to Determine the Main Contributing Factors to Carbon Neutrality across Sectors

This paper uses decomposition analysis to investigate the key contributions to changes in greenhouse gas emissions in different scenarios. We derive decomposition formulas for the three highest-emitting sectors: power generation, industry, and transportation (both passenger and freight). These formulas were applied to recently developed 1.5 °C emission scenarios by the Integrated Model to Assess the Global Environment (IMAGE), emphasising the role of renewables and lifestyle changes. The decomposition analysis shows that carbon capture and storage (CCS), both from fossil fuel and bioenergy burning, renewables and reducing carbon intensity provide the largest contributions to emission reduction in the scenarios. Efficiency improvement is also critical, but part of the potential is already achieved in the Baseline scenario. The relative importance of different emission reduction drivers is similar in the OECD (characterised by relatively high per capita income levels and emissions) and non-OECD (characterised by relatively high carbon intensities of the economy) region, but there are some noteworthy differences. In the non-OECD region, improving efficiency in industry and transport and increasing the share of renewables in power generation are more important in reducing emissions than in the OECD region, while CCS in power generation and electrification of passenger transport are more important drivers in the OECD region.

Methods and models of estimating energy transition on the example of Zhytomyr united territorial community

The paper presents results of scenario modelling and assessment of energy transition to 2050 in the Zhytomyr territorial community (TC), which provides for a switching from fossil carbon based energy resources in the current TC energy system functioning to 100% use of renewable energy sources (RES) which meets all energy demands and supports the Sustainable Development of TC in accordance with the relevant UN goals. For this purpose, the optimizational economic and mathematical TIMES-Zhytomyr model (no analogues in Ukraine), based on the TIMES-Ukraine model, was developed. It includes 647 energy technologies that are currently available or may be presented in the coming years in Ukrainian market. For the development of the TIMES-Zhytomyr model, a low-available local energy statistics was processed. As a result, the first energy balance by the form of the International Energy Agency for the large Ukrainian city and the basic energy-technological system of Zhytomyr TC were developed. Using the TIMES-Zhytomyr model, based on foreign and Ukrainian experience, for the first time, four scenarios of Zhytomyr TC energy system development were designed and modelled, covering all economic sectors and household sector (population). The first one is the Baseline scenario, which displays the possible dynamics of the energy system development without a purposeful energy efficiency policy, the development of RES, etc. Three other scenarios are aimed at studying TC’s transition capabilities by 2050 to 100% renewable energy and environmentally friendly technologies use. The results of modelling confirmed that the available renewable energy resource and technological potential allows Zhytomyr TC to perform the energy transition to 2050 in an economically feasible and socially acceptable way, significantly reducing energy and carbon intensity of the local economy, substantially eliminating GHG emissions, increasing the welfare of citizens and creating at least 10 thousand new workplaces. It will also significantly contribute to Zhytomyr TC to reach at least 10 of the 17 UN Sustainable Development Goals. The research results presented, due to a significant novelty and large-scale relevance of the task, are essential in both the theoretical and practical significance. They can be used by scientists for their research and by authorities and experts for development of local, regional or national level strategies, plans or programs of economic, energy, transport, climate and ecology scope. It can also be considered as one of the first steps in preparation of a comprehensive strategy for the Zhytomyr TC development to achieve climate neutrality in accordance with the current objectives of the European Union.

Impact of Urban Expansion On Carbon Storage Under Multi-Scenario Simulations In Wuhan, China

Carbon storage in terrestrial ecosystems, which is the basis of the global carbon cycle, reflects the changes in the environment due to anthropogenic impacts. Rapid and effective assessment of the impact of urban expansion on carbon reserves is vital for the sustainable development of urban ecosystems. Previous studies lack research regarding different scenarios during future city and comprehensive analysis on the driving factors from the socioeconomic point of view. Therefore, this study examined Wuhan, China and explored the latent effects of urban expansion on terrestrial carbon storage by combining the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and Patch-generating Land Use Simulation (PLUS) model. Based on different socioeconomic strategies, we developed three future scenarios, including Baseline Scenario (BS), Cropland Protection Scenario (CP), and Ecological protection Scenario (EP), to predict the urban built-up land use change from 2015 to 2035 in Wuhan and discussed the carbon storage impacts of urban expansion. The result shows that: (1) Wuhan's urban built-up land area expanded 2.67 times between 1980 and 2015, which is approximately 685.17 km2 and is expected to continuously expand to 1,349–1,945.01 km2 by 2035. (2) Urban expansion in Wuhan has caused carbon storage loss by 5.12×106 t during 1980–2015 and will lead to carbon storage loss by 6.15×106 t, 4.7×106 t, and 4.05×106 t under BS, CP, and EP scenarios from 2015 to 2035, accounting for 85.42%, 81.74%, and 78.79% of the total carbon loss, respectively. (3) The occupation of cropland by urban expansion is closely related to the road system expansion, which is the main driver of carbon storage reduction from 2015 to 2035. (4) We expect that by 2035, the districts facing carbon loss caused by the growth of urban built-up land will expand outward around secondary roads, and the scale of outward expansion under various scenarios will be ranked as: BS >CP > EP. In combination, the InVEST and the PLUS model can assess the impact of urban expansion on carbon storage more efficiently and is conducive to carrying out urban planning and promoting a dynamic balance between urban economic development and human well-being.

Future Climate Change Impact on the Nyabugogo Catchment Water Balance in Rwanda

Droughts and floods are common in tropical regions, including Rwanda, and are likely to be aggravated by climate change. Consequently, assessing the effects of climate change on hydrological systems has become critical. The goal of this study is to analyze the impact of climate change on the water balance in the Nyabugogo catchment by downscaling 10 global climate models (GCMs) from CMIP6 using the inverse distance weighting (IDW) method. To apply climate change signals under the Shared Socioeconomic Pathways (SSPs) (low and high emission) scenarios, the Soil and Water Assessment Tool (SWAT) model was used. For the baseline scenario, the period 1950–2014 was employed, whereas the periods 2020–2050 and 2050–2100 were used for future scenario analysis. The streamflow was projected to decrease by 7.2 and 3.49% under SSP126 in the 2020–2050 and 2050–2100 periods, respectively; under SSP585, it showed a 3.26% increase in 2020–2050 and a 4.53% decrease in 2050–2100. The average annual surface runoff was projected to decrease by 11.66 (4.40)% under SSP126 in the 2020–2050 (2050–2100) period, while an increase of 3.25% in 2020–2050 and a decline of 5.42% in 2050–2100 were expected under SSP585. Climate change is expected to have an impact on the components of the hydrological cycle (such as streamflow and surface runoff). This situation may, therefore, lead to an increase in water stress, calling for the integrated management of available water resources in order to match the increasing water demand in the study area. This study’s findings could be useful for the establishment of adaptation plans to climate change, managing water resources, and water engineering.

Spatio-Temporal Modeling of Immune Response to SARS-CoV-2 Infection

COVID-19 is a disease occurring as a result of infection by a novel coronavirus called SARS-CoV-2. Since the WHO announced COVID-19 as a global pandemic, mathematical works have taken place to simulate infection scenarios at different scales even though the majority of these models only consider the temporal dynamics of SARS-COV-2. In this paper, we present a new spatio-temporal within-host mathematical model of COVID-19, accounting for the coupled dynamics of healthy cells, infected cells, SARS-CoV-2 molecules, chemokine concentration, effector T cells, regulatory T cells, B-lymphocytes cells and antibodies. We develop a computational framework involving discretisation schemes for diffusion and chemotaxis terms using central differences and midpoint approximations within two dimensional space combined with a predict–evaluate–correct mode for time marching. Then, we numerically investigate the model performance using a list of values simulating the baseline scenario for viral infection at a cellular scale. Moreover, we explore the model sensitivity via applying certain conditions to observe the model validity in a comparison with clinical outcomes collected from recent studies. In this computational investigation, we have a numerical range of 104 to 108 for the viral load peak, which is equivalent to what has been obtained from throat swab samples for many patients.