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Excessive particle concentrations during heating periods, which greatly affect people's physical and mental health and their normal lives, continue to be a concern. It is more practical to understand and analyze the relationship between the fractal dimension and particle size concentration distribution of atmospheric particulate matter before and after adjusting heating energy consumption types. The data discussed and analyzed in this paper were collected by monitoring stations and measured from 2016 to 2018 in Xi'an. The data include fractal dimension and particle size concentration changes in the atmospheric particulate matter before and after adjusting the heating energy consumption types. The results indicate that adjusting the heating energy consumption types has a significant impact on particulate matter. The average concentration of PM2.5 decreased by 26.4 μg/m3. The average concentration of PM10 decreased by 31.8 μg/m3. At the same time, the different particle sizes showed a downward trend. The particles ranging from 0.265 to 0.475 μm demonstrated the maximum decrease, which was 8.80%. The heating period in Xi'an mainly involves particles ranging from 0 to 0.475 μm. The fractal dimensions of the atmospheric particulate matter before and after adjusting the heating energy consumption types were 4.809 and 3.397, respectively. After adjusting the heating energy consumption types, the fractal dimension decreased by 1.412. At that time, the proportions of particle sizes that were less than 1.0 μm, 2.0 μm, and 2.5 μm decreased by 1.467%, 0.604%, and 0.424%, respectively. This paper provides new methods and a reference value for the distribution and effective control of atmospheric particulate matter by adjusting heating energy consumption types. [ABSTRACT FROM AUTHOR]

Under the influence of the dual policies of sustainable economic development and the national dual-carbon target, the establishment of an environmental protection department for the treatment of heavily polluting industries is imminent, and the country has launched pollution control policies and regulations to restrict the emission rights of heavily polluting industries. Therefore, this paper focuses on whether the restriction of emission rights in key industries has reduced carbon emissions. To achieve this, this paper uses panel data of prefecture-level cities in China from 2006 to 2019 and adopts a two-way fixed-effects DID model to systematically analyze the impact of the key pollution industry governance policies launched by the Ministry of Environmental Protection on CO2 emissions in 2017. And further analyze the role of variables such as green technology innovation patents and energy efficiency using this model, while parallel trend tests and placebo tests, and related policies are used to ensure the robustness of the regression results. This paper reveals that: (1) The heavy pollution industry governance policy implemented in 2017 can effectively reduce CO2 emissions in the cities of the treated group, and the effect is more significant in the year of policy implementation; (2) Green utility patents and energy-use efficiency are the effective mediating mechanisms to reduce CO2 emissions; (3) Over time, the effect of heavy pollution industry governance policy on CO2 emissions gradually decreases; (4) The reliability of the baseline regression results of this paper is proved by the use of parallel trend tests, placebo tests, and tests excluding the influence factors such as relevant policies in the same period. Therefore, the key polluting industries treatment policy launched by China's Ministry of Environmental Protection in 2017 under the recent dual-carbon policy development goals formulated by China, can effectively reduce carbon emissions; however, in the future economic development process, the government should give more consideration to the continuity of the policy impact and its coherence on economic development when implementing the policy. [ABSTRACT FROM AUTHOR]

There is currently no way for subway air-conditioning systems to adjust to changes in passenger capacity in terms of air-supply volume and air-supply temperature. In this paper, a study of the setting of the air-supply volume and controlling the temperature in subway trains was conducted. Based on the fact that the air-supply volume in a subway train needs to meet the requirements of cooling load and humidity load, as well as fresh-air volume, the minimum critical air-supply volume curve was determined on the basis of theoretical calculations under different passenger capacities. Under different passenger capacity and air-supply-volume conditions, the PMV (predicted mean vote) distribution of the subway train was simulated and calculated, and the results indicated that increasing the air-supply volume would not be sufficient to achieve PMV = 0. Therefore, in accordance with the theoretical formulation of the PMV, multiple linear regression was used to fit the temperature-control curve for various passenger capacities. A simulation calculation of the subway train was used to assess the uniformity of the flow field and the temperature field within the subway train in accordance with EN14750. It is evident from the results that under the control curve of the air-supply volume and temperature under different passenger capacities, the uniformity of the flow field and the temperature field can meet the standard requirements. By using the air-supply volume and temperature-control curve proposed in this paper, it is possible to adjust the air-supply volume in real-time, control the temperature of the air-conditioning system of the subway train, improve the passenger comfort of the train, and reduce the energy consumption of the air-conditioning system. [ABSTRACT FROM AUTHOR]

The paper focuses on the area of experimental measurements for monitoring the impact of decarbonization on the technical and environmental parameters of the ICE. The condition for the implementation of the measurements was the selection of an ICE that had driven more than 300,790 km. During the laboratory tests, several test methods were used to assess the technical and emission conditions of the tested ICE with the code designation ALH, which is used in VOLKSWAGEN BORA vehicles. The technical parameters of the tested ICE (corrected power PNorm and torque MMom), emission parameters (absorption coefficient k and NOx emission) and fuel consumption parameters (specific fuel consumption bsfc) were compared and evaluated in the results. The results show that the decarbonization process on the tested vehicle VOLKSVWAGEN BORA 1.9 TDi affected the emission parameters but did not affect the technical parameters and specific fuel consumption. [ABSTRACT FROM AUTHOR]

Hybrid Electric Vehicles (HEVs) are a prominent solution for reducing CO2 emissions from transport in Europe. They are equipped with at least two propulsion energy converters, an Internal Combustion Engine (ICE) and one or more Electric Machines (EMs), operated in a way to exploit synergies and achieve fuel efficiency. Because of the variety in configurations and strategies, the use of simulation is essential for vehicle development and characterisation of energy consumption. This paper introduces a novel simulation approach to estimate the CO2 emissions from different hybrid architectures (series, parallel, power-split) and electrification degrees (mild, full, plug-in and range extender) that is relatively simple, flexible and accurate. The approach identifies the optimal power split between the energy converters for any given time in a driving cycle according to three evaluation levels: supervisor, ICE manager and optimiser. The latter relies on the Equivalent Consumption Minimisation Strategy (ECMS) and the limitations imposed by the other two layers. Six light-duty HEVs with different hybrid architectures were tested to support the development of the approach. The results show an indicative accuracy of ±5%, enabling to run assessments of hybrid powertrain solutions and supporting regulatory and consumer information initiatives. [ABSTRACT FROM AUTHOR]

The paper utilized a panel dataset to investigate the effects of the impact factors, namely, economic growth, energy intensity, energy consumption, urbanisation, passenger vehicles and transport infrastructure investments on carbon emissions (CO2-eq). The transport sector of the main buoyant economic provinces of South Africa for a consecutive period of five years was investigated using STIRPAT models. Carbon emissions coefficient method, (CECM) is made applicable to determine the quantification of the forms of fossil fuels utilized in the transportation sector. The characterized parametric panel dataset for Gauteng, KwaZulu-Natal and Western Cape were assessed from 2016 to 2020 to make objective function determinations. The results indicate that GDP and passenger vehicles contributed largely to CO2-eq emissions, however, the impact varies across the three provinces. Energy intensity and the approach to energy consumption are significant in mitigating carbon emissions, which is due to the possibilities of high fuel efficiency and pollution decrease. The outcome of the research advances climate change mitigation strategy and proffers the required attention to policy makers in South Africa and Africa as a continent. [ABSTRACT FROM AUTHOR]

Growing global concern over greenhouse gas emissions has led to a demand for understanding and addressing carbon emissions, with China being one of the main contributors to global carbon emissions, committed to reach the carbon peak by 2030. As a result, much previous research has delved into the drivers of carbon emissions in China; however, few studies have included new energy factors in the extended STIRPAT model when analysing the data, employed more advanced visualisation techniques such as force-directed diagrams, and explored factors outside of the industrial and energy sectors in determining China's ability to reach their environmental goals. In this study, we use the extended STIRPAT model to analyse a more diverse range of drivers for carbon emissions in China and discuss methods to reach peak carbon emissions through the implementation of environmental policies. Using data from China's 14th Five-Year Plan and Vision 2035 to set up two simulation scenarios, we predict China's carbon emissions, introducing ridge regression to ensure validity, and employing big data and visualisation techniques to aid in interpreting results. Our findings suggest that China needs to implement more stringent environmental policies to meet its commitment to reach peak carbon emissions by 2030, revealing that factors such as per capita arable land area, per capita GDP, the proportion of people living in extreme poverty, the level of tourism development, the use of fossil fuels, and new energy technologies have a significant impact on China's carbon emissions. As such, we can recommend more stringent policies relating to the agricultural, energy, and tourism sectors to help China achieve their goal of carbon peak by 2030. [ABSTRACT FROM AUTHOR]

Climate change has become a global issue and is predicted to impact less-developed regions, such as sub-Saharan Africa, severely. Innovative, sustainable renewable energy systems are essential to mitigate climate change's effects and unlock the region's potential, especially with the increasing energy demands and population growth. The region relies heavily on fossil fuels, which calls for urgent action towards energy security and expansion. Hybrid floating solar photovoltaic-hydropower (FPV-HEP) technology has emerged as a cost-effective and transformative solution to accelerate the low-carbon energy transition in sub-Saharan Africa. The technology combines solar panels with existing hydropower infrastructure, ensuring energy security while reducing carbon emissions. This technology offers several benefits over conventional ground-mounted solar systems, including efficient land utilization, energy generation, and water conservation. However, its adoption remains challenging due to technical complexities and evolving regulatory frameworks. Despite these challenges, Nigerian energy professionals have preferred renewable alternatives, mainly distributed solar PV and FPV-HEP plants. This collective embrace of FPV and renewables reflects a growing understanding of their critical role in mitigating climate change through sustainable energy practices. This research aims to contribute to the existing body of knowledge and assist policymakers in making informed decisions on adopting this technology. It also stimulates further research on this topic, offering a new potential solution to the ever-increasing demand for green energy in the region to meet their sustainable development needs. [ABSTRACT FROM AUTHOR]

Nowadays, indoor air quality (IAQ) and the energy performance of buildings are two main scientific and technical challenges because they are in direct connection with human health and the depletion of energy resources. In this study, we analyzed the influence of an outdoor air flow introduced through a mechanical ventilation system, focusing on the two aforementioned topics. A standardized ventilation rate (25 m3/h/person) led to an increase in the indoor O3 concentration (from 5 μg/m3 to 50 μg/m3) and, simultaneously, to a decrease in the indoor CO2 concentration (from 2000 mg/m3 to 800 mg/m3), a decrease in the PM2.5 concentration (from 300 μg/m3 to 150 μg/m3), and the maintenance of a constant indoor HCHO concentration. In our study, a new, single indoor air quality index, IIAQ, is proposed. This new index presents different implications: on the one hand, it has the ability to simultaneously take into account several pollutant species, and on the other hand, it can prioritize the ventilation strategy that responds to the extreme values of a certain pollutant. Moreover, indoor air quality classes were elaborated, similar to energy classes. The possibility of using this new index simultaneously with energy consumption may lead to ventilation strategies that are adaptative to dynamic outdoor pollutant concentrations. [ABSTRACT FROM AUTHOR]

Climate change is expected to significantly affect countries in Southern Europe and the Mediterranean Basin, causing higher-than-average temperature increases, considerable reductions in rainfall and water runoff, and extreme events such as heatwaves. These pose severe threats to local energy systems, requiring a reliable and quantitative risk analysis. A methodological approach is thus proposed which covers both energy supply and demand, utilizing the latest climate projections under different greenhouse gas emissions scenarios and an appropriate scale for each energy form. For energy supply technologies, risks are assessed through statistical regression models and/or mathematical equations correlating climatic parameters with energy productivity. To analyze climate risks for energy demand, bottom–up models were developed, integrating both behavioral and policy aspects which are often considered in a very limited way. The results show that climate change will mainly affect electricity generation from hydroelectric and thermal power plants, with variations depending on the plants' locations and uncertainties associated with precipitation and runoff changes. The climate risks for solar and wind energy were found to be low. Energy consumption will also be affected, but the range of risks depends on the ambition and the effectiveness of measures for upgrading the thermal performance of buildings and the intensity of climate change. [ABSTRACT FROM AUTHOR]

The National Standard of China has recommended the typical meteorological year (TMY) method for assessing solar energy resources. Compared with the widely adopted multi-year averaging (MYA) methods, the TMY method can consider the year-to-year variations of weather conditions and characterize solar radiation under climatological weather conditions. However, there are very few TMY-based solar energy assessments on the scale of China. On the national scale, the difference between the TMY and MYA methods, the requirement of the data record length, and the impacts of the selection of meteorological variables on the TMY-based assessment are still unclear. This study aims to fill these gaps by assessing mainland China's solar energy resources using the TMY method and China Meteorological Forcing Dataset. The results show that the data record length could significantly influence annual total solar radiation estimation when the record length is shorter than 30 years. Whereas, the estimation becomes stable when the length is greater or equal to 30 years, suggesting a thirty-year data record is preferred. The difference between the MYA and TMY methods is exhibited primarily in places with modest or low abundance of solar radiation. The difference is nearly independent of the examined data record lengths, hinting at the role of regional-specific weather characteristics. The TMY and MYA methods differ more pronounced when assessing the seasonal stability grade. A total of 7.4% of the area of China experiences a downgrade from the TMY relative to the MYA methods, while a 3.15% area experiences an upgrade. The selection of the meteorological variables has a notable impact on the TMY-based assessment. Among the three meteorological variables examined, wind speed has the most considerable impact on both the annual total and seasonal stability, dew point has the second most significant impact, and air temperature has the least. The results are useful for guiding future research on solar energy assessment in China and could be helpful for solar energy development planning. [ABSTRACT FROM AUTHOR]

Regional energy development and approaches are significant for China's overall economic and social development. The GDP in Zhejiang province surpassed 6 trillion yuan in 2019, and its energy consumption reached 200 million tons of standard coal (tce), both of which are at the forefront of China. In order to explore the main factors of the increase in energy consumption in Zhejiang and provide essential references for energy saving and other provinces, this paper analyzes the total energy consumption and industrial sectors on the basis of the logarithmic mean divisia index (LMDI) model. Study results show that the economy's scale is the most crucial factor affecting Zhejiang's energy consumption, with a significant growth effect. In 2015, the scale effect increased energy consumption to the highest value of 14 million tce and then reduced it to 13 million tce in 2019. The impact of the population on energy consumption increased by 10 million tce from 2010 to 2019. Energy intensity reduces energy consumption by between 0.05 and 0.15 billion tce per year, which is the main factor in reducing energy consumption. The energy structure generally plays a weak positive role due to the different energy types. The decomposition of the energy consumption per unit of value added in the industrial sector showed that the intensity and structural effect primarily reduce energy consumption, for example, the metal smelting and rolling, textile printing and paper, electric power, heating, and other industries. According to the results, enterprises should enhance the intelligence and efficiency of dispatch management and emergency responses. Zhejiang should also accelerate an international oil and gas trading center and resource allocation base to reach its carbon-neutrality goal. [ABSTRACT FROM AUTHOR]

By using space-based measurements of the column-averaged dry air mole fraction of carbon dioxide (XCO2) from the Orbiting Carbon Observatory-2 (OCO-2) and CO and NO2 from the Tropospheric Monitoring Instrument (TROPOMI), this study investigates the seasonal variation in the characteristics of CO2, CO, and NO2 across major states in the United States. Beyond correlating these trends with natural factors, significant emphasis is placed on human activities, including heating demands, energy usage, and the impacts of the COVID-19 pandemic. Concentration enhancements in observations influenced by anthropogenic emissions from urban regions relative to background values are calculated to estimate gas emissions. Our investigation reveals a strong correlation between NO2 and CO2 emissions, as evidenced by a correlation coefficient (r) of 0.75. Furthermore, we observe a correlation of 0.48 between CO2 and CO emissions and a weaker correlation of 0.37 between CO and NO2 emissions. Notably, we identify the NO2 concentration as a reliable indicator of CO2 emission levels, in which a 1% increase in NO2 concentration corresponds to a 0.8194% (±0.0942%) rise in annual mean CO2 emissions. Enhancement ratios among NO2, CO, and XCO2 are also calculated, uncovering that high ΔNO2: ΔXCO2 ratios often signify outdated industrial structures and production technologies, while low ΔCO: ΔXCO2 ratios are linked to states that utilize clean energy sources. This approach offers a deeper understanding of the effect of human activities on atmospheric gas concentrations, paving the way for more effective environmental monitoring and policy-making. [ABSTRACT FROM AUTHOR]

The harsh scientific research environment of Antarctic stations demands a reliable energy supply; however, traditional methods not only pose a challenge in supply but also harm the environment. Antarctic energy supply has become a new choice for energy development in Antarctica due to its abundant wind energy resources. Using ERA5 10 m wind field reanalysis data, we compared and analyzed the correlation (r) and Root Mean Square Error (RMSE) between some observation stations and reanalysis data, with correlations above 0.67 and root mean square error below 2.3. This indicates that the accuracy of the ERA5 data is suitable for resource assessment at stations in Antarctica. We assessed the wind energy potential of the Great Wall, Zhongshan, Kunlun and Taishan Stations. The results show that the annual distribution and long-term trend of wind energy at Taishan Station are the best, followed by the Great Wall, Zhongshan and Kunlun Stations. Taishan Station has stable wind direction and abundant wind energy, the average wind power density is 800 W/m2, with an annual growth trend of 2.02 W/m2·yr−1. The effective wind speed occurrence and energy level occurrence are generally above 90% and the coefficient of variation is generally below 0.8. The dominant direction of wind energy is northeast and the wind direction is stable, which is conducive to the development and utilization of wind energy. [ABSTRACT FROM AUTHOR]

Regional energy development and approaches are significant for China’s overall economic and social development. The GDP in Zhejiang province surpassed 6 trillion yuan in 2019, and its energy consumption reached 200 million tons of standard coal (tce), both of which are at the forefront of China. In order to explore the main factors of the increase in energy consumption in Zhejiang and provide essential references for energy saving and other provinces, this paper analyzes the total energy consumption and industrial sectors on the basis of the logarithmic mean divisia index (LMDI) model. Study results show that the economy’s scale is the most crucial factor affecting Zhejiang’s energy consumption, with a significant growth effect. In 2015, the scale effect increased energy consumption to the highest value of 14 million tce and then reduced it to 13 million tce in 2019. The impact of the population on energy consumption increased by 10 million tce from 2010 to 2019. Energy intensity reduces energy consumption by between 0.05 and 0.15 billion tce per year, which is the main factor in reducing energy consumption. The energy structure generally plays a weak positive role due to the different energy types. The decomposition of the energy consumption per unit of value added in the industrial sector showed that the intensity and structural effect primarily reduce energy consumption, for example, the metal smelting and rolling, textile printing and paper, electric power, heating, and other industries. According to the results, enterprises should enhance the intelligence and efficiency of dispatch management and emergency responses. Zhejiang should also accelerate an international oil and gas trading center and resource allocation base to reach its carbon-neutrality goal.

Densely built areas with poor thermal insulation suffer from high thermal environmental risks and generally consume high energy in summer. Determining the relationship between density and energy consumption is necessary, particularly when implementing urban heat island (UHI) countermeasures. This study evaluated the effects of density and UHI countermeasures on the energy consumption and indoor thermal comfort of a detached house in a typical densely built wooden house area in Yokohama City, Japan. Three densities and six countermeasures were considered. Annual hourly simulations based on the SCIENCE-Vent thermal environment simulation model yielded the following results: in densely built wooden house areas, the energy consumption and thermal discomfort increased with density. The green roof yielded the largest energy savings in the cooling and heating seasons, demonstrating the highest annual energy savings with 5.7%. Density had little impact on rooftop countermeasures, but the effect of the high-reflectance walls increased with density, and the reduction in annual energy consumption (air conditioning and lighting) is 2.6%, 3.0%, 3.6% in 37%, 47%, and 59% density cases, respectively. The impact of thermal countermeasures on indoor thermal comfort varied according to the thermal control mechanism. [ABSTRACT FROM AUTHOR]

Reactive nitrogen (Nr) has been confirmed as an indispensable nutrient for the city ecosystem, but high-intensity human activities have led to nitrogen pollution in cities, especially in coastal cities, jeopardizing ecosystem services and human health. Despite this, the characteristics and influencing factors of Nr remain unclear in coastal cities, particularly in the context of rapid urbanization. This study used the material flow analysis method to estimate Nr emissions in Xiamen from 1995 to 2018 and evaluated the characteristics of excessive Nr emissions. The STIRPAT model was used to identify and explore factors contributing to observed Nr levels in coastal cities. As indicated by the results, (1) the quantity of Nr generated by human activities increased 3.5 times from 1995 to 2018. Specifically, the total Nr entering the water environment showed a general increase with fluctuations, exhibiting an average annual growth rate of 3.1%, increasing from 17.2 Gg to 35.1 Gg. (2) Nr loads in the nearby sea increased notably from 8.1 Gg in 1995 to 25.4 Gg in 2018, suggesting a threefold augmentation compared with surface waters and groundwater. (3) NOx was the gaseous Nr with the greatest effect on the atmosphere in Xiamen, which was primarily due to fossil fuel consumption. (4) Population and per capita GDP were major factors contributing to Nr load in the water environment, while Nr emission to the atmosphere was influenced by population and energy consumption. These findings provide valuable insights for tailored approaches to sustainable nitrogen management in coastal cities. [ABSTRACT FROM AUTHOR]

Controlling NOx and CO2 emissions from heavy-duty diesel vehicles (HDDVs) is receiving increasing attention. Accurate measurement of HDDV NOx and CO2 emissions is the prerequisite for HDDV emission control. Vehicle emission regulations srecommend the measurement of NOx and CO2 emissions from vehicles using an emission analyzer, which is expensive and unsuitable to measure a large number of vehicles in a short time. The on-board diagnostics (OBD) data stream of HDDVs provides great convenience for calculating vehicle NOx and CO2 emissions by providing the engine fuel flow rate, NOx sensor output, and air mass flow. The calculated vehicle NOx and CO2 emissions based on the OBD data were validated by testing a heavy-duty truck's emissions on the chassis dynamometer over the CHTC-HT driving cycle, showing that the calculated NOx and CO2 emissions based on the OBD data are consistent with the measured results by the emission analyzer. The calculated vehicle fuel consumptions based on the OBD data were close to the calculated results based on the carbon balance method and the measured results by the fuel flowmeter. The experimental results show that accessing vehicle NOx and CO2 emissions based on the OBD data is a convenient and applicable method. [ABSTRACT FROM AUTHOR]

Urban public buildings carbon emissions exhibit an upward trend and have a large potential in carbon emission reduction. The analysis of spatiotemporal characteristics and driving factors for urban public buildings carbon emissions is essential in formulating effective policies for carbon reduction, meeting commitments to peak carbon emissions and achieving carbon neutrality. This study takes China's urban public buildings carbon emissions as the research object, employing methods such as spatial autocorrelation analyses, kernel density estimation analyses, and the LMDI decomposition methods to explore the spatiotemporal characteristics and regional disparities in carbon emissions from 2006 to 2019. Furthermore, it quantifies the contributions of driving factors to the spatiotemporal changes in urban public buildings carbon emissions. The results show the following: (1) Urban public buildings carbon emissions among provinces are consistently increasing, indicating an overall upward trend. The spatial distribution highlights significant regional disparities. (2) The spatial characteristics of urban public buildings carbon emissions were basically stable. The eastern coastal regions demonstrate a high-high cluster, while the western regions exhibit a low-low cluster. The overall cluster evolution showed a decreasing trend from east to west. (3) Per capita urban public building area, economic density, urbanization rate, and population size serve as driving factors for carbon emissions from urban public buildings, while energy efficiency and energy consumption intensity act as inhibitory factors. The findings of this research can assist policymakers in getting a deeper comprehension of urban public buildings carbon emissions and providing a scientific basis to formulate appropriate carbon emission reduction policies. [ABSTRACT FROM AUTHOR]

While there is strong demand for cement because of its widespread use in modern society, its production is a source of international concern due to the large amounts of energy required and the greenhouse gas (GHG) emissions produced in the process. These GHGs deplete the ozone layer and speed up global warming. Therefore, it is important to investigate several methods of handling this issue, and material replacement has been proposed as the best option among many others. In this study, we examine the different strategies that have employed material substitution to reduce energy use and GHG emissions during the past decade. In this study, we provided an overview of the cement production processes and outlined the various material replacement choices available to us (including waste or recycled materials and other materials). This study found that partial (1–60%) and total material substitution in cement production processes have been reported to lower energy consumption by 5.5% to 40% and greenhouse gas emissions by 1% to 94%. This highlights the importance of material substitution in cement production for reducing energy consumption and emissions of greenhouse gases. [ABSTRACT FROM AUTHOR]

With the deepening of urbanization and industrialization, as well as the exacerbation of energy consumption, China is facing a severe situation in which nitrogen oxide (NOx) emissions reduction is imperative. In this study, it is aimed to put forward countermeasures and suggestions to reduce NOx emissions by analyzing the impact and mechanism of new urbanization, the agglomeration of energy-intensive industries and mutual interactions on China's NOx emissions. By analyzing the data of 30 provinces in China from 2006 to 2017, this paper adopted the system generalized method of moments (SYS-GMM) and intermediary effect model to introduce four variables, such as: energy efficiency, human capital, industrial structure and energy structure, which were for empirical analysis. From the results, it was shown that: (1) NOx emissions in China have an accumulated effect; (2) new urbanization inhibits NOx emissions, whilst the agglomeration of energy-intensive industries intensifies NOx emissions. New urbanization weakens the negative impact of the agglomeration of energy-intensive industries on NOx emissions reduction and, (3) among the impacts of new urbanization on NOx emissions, the energy efficiency and human capital reflect the intermediary effect mechanism. At the same time, in the impact of the agglomeration of energy-intensive industries on NOx emissions, the industrial structure and energy structure show the mechanisms of the intermediary effect and masking effect, respectively. [ABSTRACT FROM AUTHOR]

More than 50% of the world's population lives in cities. Its buildings consume more than a third of the energy and generate 40% of the emissions. This makes cities in general and their buildings in particular priority points of attention for policymakers and utilities. This paper uses population density as a variable to know its influence on energy consumption and emissions produced in buildings. Furthermore, to show its effect more clearly, the influence of the climate was eliminated. The usual energy consumption in buildings is thermal and electrical. The study was carried out at the city level, both per inhabitant and per household. The area actually occupied by the city was considered. The proposed method was applied to the case of Spanish cities with more than 50,000 inhabitants. The results show that the higher the population density, the higher the energy consumption per inhabitant and household in buildings. The consumption of thermal energy is elastic, while that of electrical energy is inelastic, varying more than 100% between extreme groups. Regarding CO2 emissions, the higher the population density, the higher the emissions. Emissions of electrical origin barely vary by 2% and are greater than those of thermal origin. In addition, the proportion of emissions of electrical origin, with respect to the total, decreases with increasing population density from 74% to 55%. This research aims to help policymakers and utilities to take the appropriate measures that favor the use of renewable energies and reduce CO2 emissions. [ABSTRACT FROM AUTHOR]

Roof surfaces on which air conditioning equipment is installed cause significant air temperature increases around the condensers due to roof thermal properties, resulting in excess electrical energy consumption and greenhouse gas (GHG) emissions. An experiment to quantify such excesses during the summer was conducted at a university campus in Mexicali, Mexico. The air temperatures and surface temperatures for three types of roofs were recorded. Temperatures (condenser inlet air temperatures) were used as the input data to a priori estimate the electrical consumption of a 5-ton A/C equipment working over these different roofs. Temperatures recorded by a nearby meteorological station were used as a reference. The results indicate a differential of up to 4.81 °C, resulting in an excess of electricity consumption of 5.55 kWh and an additional 3.9 kg of CO2 emissions, representing an 8.2% energy surplus and differences of up to 2.1% in electricity consumption provoked by microclimate. [ABSTRACT FROM AUTHOR]

The mitigation strategies and actions for mitigating the emission of greenhouse gas (GHG) from the energy sector become more important and urgent. The main aim of this paper was to present a trend analysis of the emissions of GHG from the Taiwan's energy sector, which was issued by the central competent authority through the Intergovernmental Panel on Climate Change (IPCC) methodology. The data also complied with the procedures of measurement, reporting and verification. Based on the official database, the statistics on energy supply, energy consumption and GHG emissions will be connected to analyze the trends of environmental and energy sustainability indicators over the past decades. It showed that the trends of the relevant sustainability indicators based on GHG emissions from the energy sector indicated two development stages: the growth period (annually 5.6%) of 1990–2005, and the decoupling period (annually 0.5%) of 2005–2018. This result could be ascribed to the Taiwan government by promulgating some regulatory measures on energy saving improvement and renewable energy supply during this period. It was worthy to note that the installed capacities of photovoltaic (PV) power increased from 888 megawatt (MW) in 2015 to 5817 MW in 2020. These technological, behavioral, managerial and policy advancements are in accordance with global mitigation strategies. Under the authorization of the energy-related regulations, some promotional actions or programs for efficient energy use and renewable electricity supply were also announced to reach the targets of GHG emissions reduction in the sustainable development goals (SDGs). [ABSTRACT FROM AUTHOR]

Using a one-dimensional code, we computed the power (enthalpy discharge rate) of a twelve-cell mechanical draft cooling tower (MDCT) using over two hundred visible condensed water vapor plume volume measurements derived from images, weather data, and tower operating conditions. The plume images were simultaneously captured by multiple stationary digital cameras surrounding the cooling tower. An analysis technique combining structure from motion (SfM), a neural-network-based image segmentation algorithm, and space carving was used to quantify the volumes. Afterwards, the power output was computed using novel techniques in the one-dimensional code that included cooling tower exhaust plume adjacency effects implemented with a modified version of the entrainment function, weather data averaged from eleven stations, and fan operations at the times when plume volumes were measured. The model was then compared with the averaged observed power output, and it validated well with an average error ranging from 6 to 12%, depending on the meteorological data used in the simulations. This methodology can possibly determine power plant fuel consumption rates by applying visible imagery. [ABSTRACT FROM AUTHOR]

This study aims to investigate the spatio-temporal distribution, variation, abrupt change, and long-term trends of major pollutant emissions in the Kingdom of Saudi Arabia (KSA) over the period 1960–2020 using the Monitoring Atmospheric Composition and Climate (MACC)/CityZEN EU projects (MACCity) emissions dataset inventory. These pollutants are carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), volatile organic compounds (VOCs), black carbon (BC), and organic carbon (OC). Seven stations were selected (Al-Bahah, Abha, Dahra, Jeddah, Riyadh, Qassim, and Ahsa), which correspond to the highest (hotspot) annual pollutant emissions. The annual cycle analysis of the six pollutant emissions revealed that there are four distinct patterns; the first one has one interannual wave while the other three patterns have two interannual waves. The analysis of the different sectors' contributions to pollutant emissions revealed that the energy, transportation, and industries sectors have the highest percentage contributions. Significant abrupt change points were detected in 1970, 1980, 1990, 2000, 2005, and 2010. The development and growth rates in the KSA starting from the early 1970s are attributed to the oil boom. The great increase in pollutant emissions in the early 1980s followed by that in the 1990s up to 2000 is due to an increase in fossil fuel demand, industries, transportation, and energy consumption. [ABSTRACT FROM AUTHOR]

Global warming is directly related to heavy-duty vehicle fuel consumption and greenhouse gas (CO2 mainly) emissions, which, in China, are certified on the vehicle chassis dynamometer. Currently, vast amounts of vehicle real-road data from the portable emission measurement system (PEMS) and remote monitoring are being collected worldwide. In this study, a binning-reconstruction calculation model is proposed, to predict the chassis dynamometer fuel consumption and CO2 emissions with real-road data, regardless of operating conditions. The model is validated against chassis dynamometer and PEMS test results, and remote monitoring data. Furthermore, based on the proposed model, the fuel consumption levels of 1408 heavy-duty vehicles in China are analyzed, to evaluate the challenge to meet the upcoming China fourth stage fuel consumption limits. For accumulated fuel consumption based on the on-board diagnostic (OBD) data stream, a predictive relative error less than 5% is expected for the present model. For bag sampling results, the proposed model's accuracy is expected to be within 10%. The average relative errors between the average fuel consumption and the China fourth stage limits are about 3%, 8%, and 0.7%, for current trucks, tractors, and dump trucks, respectively. The urban operating condition, with lower vehicle speeds, is the main challenge for fuel consumption optimization. [ABSTRACT FROM AUTHOR]

In accordance with national regulations, the renovation of the residential sector is an urgent task for achieving significant reductions in energy consumption and CO2 emissions of the existing building stock. Social housing is particularly in need of such interventions, given the higher vulnerability of its inhabitants and its crucial role in furthering social welfare and environmental sustainability objectives. Both passive and active strategies have proved their efficacy in advancing towards these goals and also in mitigating increasing fuel poverty in low-income families. However, to optimize the best combination of such retrofit strategies, advanced optimization methodologies can be applied. Here, a multi-objective optimization methodology is implemented by a genetic algorithm (aNSGA-II) coupled to EnergyPlus dynamic energy simulations. Then, the energy consumption of the optimal solution is considered by means of EnergyPLAN simulations for the further application of active strategies. The two-step method is tested on a relevant case study, a social housing building in Rome, Italy. Results show that the applied method reduced the energy demand by 51% with passive strategies only. Active strategy implementation allowed for a further reduction of 69% in CO2 emissions and 51% in energy costs. The two-step method proved effective in mitigating fuel poverty and decarbonizing the residential sector. [ABSTRACT FROM AUTHOR]

Under the impact of COVID-19 and the needs for urban expansion, a large number of outpatient buildings have been rapidly constructed, but the problem of high energy consumption has always been ignored. There is a lack of research on the adaptability of building shape in different climate zones. Many studies have shown that a reasonable shape in the early stage of design can significantly reduce the energy consumption of buildings. Therefore, it helps if architects quickly select a reasonable shape that can effectively reduce energy consumption. This study summarized a number of outpatient building cases in China and proposed three typical building shapes: centralized-type (Shape-1), corridor-type (Shape-2), and courtyard-type (Shape-3). The Design Builder tool was used to simulate and analyze the typical building energy consumption in different climate zones. The simulation results show that Shape-2 (angle: 0°) should be chosen in severe cold zone; Shape-1 (angle: 90°) should be chosen in cold zone; Shape-1 (angle: 0°) should be chosen in hot summer and cold winter zone; Shape-1 (angle: 60°) should be chosen in hot summer and warm winter zone; and Shape-1 or Shape-2 can be chosen in warm zone. The results of this study can provide suggestions for the energy saving design of outpatient buildings in China and other areas with similar conditions. The result can help architects make rapid shape selection in the early stage of design. [ABSTRACT FROM AUTHOR]

Dynamic building energy performance modeling is becoming increasingly important in the architectural, engineering, and construction (AEC) industry because of the sector's significant environmental impact. For such analysis, a climate file representing a typical meteorological year (TMY) is needed, including hourly values for the most important weather-related parameters. However, TMY shows little resemblance to the future of the particular location where a building has been used for decades. Therefore, using predicted future climates during building design is unfortunately rarely practiced, potentially undermining the strategies that should be the fundamental basis of the design. To explore this question, our study compared the heating and cooling energy consumption, indoor thermal comfort, and summer overheating potential of a selected building for three distinctive European climates, in Hungary, Portugal, and Lithuania. All of them were changed according to the IPCC RCP4.5 scenario, and were examined for the present, the 2050, and the 2100 scenarios. We also tested adaptive clothing to evaluate the indoor comfort parameters. The results show a 10% increase in heating and cooling energy use for the same construction and location between 2020 and 2100. The continental climate of Budapest is the most threatened by summer overheating, with an increase of 69% for the ODH26 indicator. A more balanced warming for Lisbon was found (23%), and moderate changes for the city of Kaunas (a 153% increase from a very low baseline). [ABSTRACT FROM AUTHOR]

Solar heat gain and natural ventilation cooling of the indoor environment in buildings are highly influenced by the shading and openable area of windows. In addition to the ambient condition, the Heating, ventilation and air conditioning (HVAC) system's mode of use can affect the windows' performance, especially when multiple modes are used in combination (mixed-mode). Although many studies have investigated the mixed-mode application, their conditions for starting/shutting down HVAC equipment and controlling window ventilation are inconsistent with the relevant codes. Here, we propose a mixed-mode operation that resolves the gap between the air conditioning operation temperature and the adaptive comfort upper temperature. It investigates residential buildings' indoor thermal environment and energy efficiency by combining the effective ventilation opening area ratio (REV) and shading design. Simulation results show that our mixed-mode can reduce the indoor overheating hours by about 50% and the building's energy consumption by about 50%. We thereby conclude that the openable area of exterior windows in residential buildings in Chongqing should not be less than 10% of the room's floor axis area where the exterior windows are located. In general, our study expands the existing knowledge of passive energy-saving measures and provides a method for further research on building energy design in hot summer and cold winter regions. [ABSTRACT FROM AUTHOR]

Vehicle mileage is one of the key parameters for accurately evaluating vehicle emissions and energy consumption. With the support of the national annual vehicle emission inspection networked platform in China, this study used big data methods to analyze the activity level characteristics of the light-duty passenger vehicle fleet with the highest ownership proportion. We found that the annual mileage of vehicles does not decay significantly with the increase in vehicle age, and the mileage of vehicles is relatively low in the first few years due to the run-in period, among other reasons. This study indicated that the average mileage of the private passenger car fleet is 10,300 km/yr and that of the taxi fleet was 80,000 km/yr in China in 2019, and the annual mileage dropped by 22% in 2020 due to the pandemic. Based on the vehicle mileage characteristics, the emission inventory of major pollutants from light-duty passenger vehicles in China for 2010–2020 was able to be updated, which will provide important data support for more accurate environmental and climate benefit assessments in the future. [ABSTRACT FROM AUTHOR]

Climate is a key element in building design. The determination of adequate climate zoning is crucial for achieving building energy efficiency and reduced carbon emissions. In this study, a cluster analysis method was applied to develop new thermal climate zones for building envelope thermal design in China. In total, three different cluster analysis methods, including k-means, average-linkage, and Ward's clustering, were considered. The analysis indicated that the average-linkage clustering was more appropriate for this study, and the elbow method could not accurately determine the best number of categories of average-linkage clustering. Further analysis showed that the unsupervised cluster processes may generate an unavoidable redundancy category and, to obtain precise results, supervision may be necessary in some contexts. Finally, China was classified into 10 climate zones. The North China plain and Qinghai–Tibet plateau are classified into two independent climate zones, and Turpan and Bayanbulak were classified into two newly defined climate zones different from their surrounding area in the new definition. Quantitative analysis indicated that the new zones were more precise when compared to the current ones, which can provide more precise climate information and contribute to formulating more precise standards and policies related to the thermal design of building envelopes in the future. [ABSTRACT FROM AUTHOR]

Background: The current COVID-19 pandemic has demonstrated the enormous importance of maintaining good hygienic conditions in everyday indoor environments for the prevention of infectious diseases. This includes sanitization methods capable of significantly reducing the microbial load in the air and on surfaces. However, in line with the ecological transition, alternative systems for environmental sanitization with reduced environmental impact are urgently needed. The photocatalytic reaction using UV-C light-emitting diode (UV-C LED) lamps with short wavelengths, especially in the range of 200–280 nanometers (nm), can significantly reduce the microbial load, safeguarding the environment thanks to reduced energy consumption. The objective of this review is to describe the latest innovations in the use of UV-C LED technology in the sanitization of indoor environments, reporting the fundamental principles on which its activity relies. Methods: Two databases (PubMed, Web of Science), were searched, following PRISMA guidelines. Results: A total of 1348 publications were identified, of which 379 were assessed in detail and, of these, 16 were included in the review. Conclusions: This literature review highlighted that UV-C LEDs irradiation represents a valid, eco-sustainable sanitization method that could be exploited as an alternative to chemical compounds to contain indoor microbiological pollution in living and working environments. [ABSTRACT FROM AUTHOR]

Hybrid electrostatic precipitators consisting of electrostatic precipitation (ESP) and a bag filter are potential devices for ultralow emissions. The ESP captures and charges the particles; subsequently, the charged particles that escape enter the bag filter. The charged particles can cause the electric field of the filter bag to develop, thereby enhancing the filtration efficiency due to the force of the electric field. Experiments based on the coupling-reinforced electrostatic–fabric integrated precipitator system were conducted to investigate the outlet total dust concentration, dust removal efficiency, pressure drop, energy consumption of bag filter, and hybrid electrostatic precipitators with various filter bags. The measured results demonstrate that the removal performance of filter bags with smaller fiber diameters was superior. However, the pressure drop and energy consumption were high due to the increased filtration resistance. Compared to bag filters, hybrid electrostatic precipitators had lower total and grade dust mass concentrations at the outlet, higher total and grade dust removal efficiencies, a minor average pressure drop variation per minute, and lower total energy consumption. Consequently, the quality factor was utilized to comprehensively evaluate the overall performance of dust collectors. The hybrid electrostatic precipitators had a significant greater quality factor; their overall performance was superior to that of bag filters. Overall, a smaller filter bag's fiber diameter resulted in more effective dust removal capabilities. Hybrid electrostatic precipitators with various filter bags were significantly better than bag filters in terms of dust removal performance, cycle life, and energy consumption. [ABSTRACT FROM AUTHOR]

Highlights: This study sorted out and categorized main inventory compilation methods. Five main methods were compared and characterized by their applicability, complexity, time of calculation, accuracy of results, ability to distinguish vessel types and sources of emissions. A new method was proposed to develop an emission inventory based on a vessel energy consumption reporting system. This method is believed to have the potential advantages to produce results of higher accuracy, higher temporal and spatial resolutions. Five main methods were used to calculate emission inventories in three cases at different scales. This study recommends the use of different inventory compilation methods under different circumstances. Ship exhaust emissions have been considered as a significant source of air pollution that has an adverse impact on the global climate and human health. It is of vital importance to create an accurate ship emission inventory for the purpose of formulating effective control measures. A wide range of inventory compilation methods have been proposed around the globe, and there has long been a pressing need to analyze and compare these methods in depth. This study sorted out and categorized inventory compilation methods of ship emissions in recent decades. Five main methods were compared and analyzed by their applicability, complexity, time of calculation, accuracy of results, etc. In addition, a new method was proposed to develop an emission inventory based on a vessel energy consumption reporting system. This method is believed to have the potential advantages to produce results of higher accuracy and temporal and spatial resolutions. To perform the validation, three cases at different scales were selected in part of China and surrounding maritime waters (large-scale), the Yangtze River Delta region (medium-scale), and Tianjin Port (small-scale), respectively. The analysis results show that: each of methods have different technical characteristics. Computed results significantly between methods, with the maximum deviation of up to 87%. It is advisable that the optimal method should be chosen based on the actual needs in inventory compilation and the data available. In terms of accuracy of results, Methods 1 and 5 offer moderately high accuracy; Method 2 provides average accuracy; while Methods 3 and 4 produce low accuracy. In terms of resolution of results, Methods 1 and 5 provide high-resolution temporal and spatial distribution of ship emissions; Method 2 delivers low-resolution spatial distribution; while Methods 3 and 4 are incapable of spatial distribution. In terms of applicability, Method 1 applies to the calculation of inventories of varying scales; Method 2 is more applicable to small-scale calculations, such as a port; Methods 3, 4, and 5 are more desirable for large-scale calculations, such as a country. The author recommends Methods 5, 1, 3, and 2/4 in a descending order of preference for large-scale ship emissions inventory compilations; recommends Method 5 (if accuracy is the first priority) or Method 1 (if temporal and spatial resolutions are given first priority), followed by Methods 2, 3, and 4 in a descending order of preference for small/medium-scale ship emissions inventory compilations. These results may serve to help inventory compilers choose an applicable method and support improvements in inventory compilation methods. [ABSTRACT FROM AUTHOR]

Increasingly stringent environmental requirements for marine engines imposed by the International Maritime Organisation and the European Union require that marine engines have the lowest possible emissions of greenhouse and harmful exhaust gases into the atmosphere. In this research, exhaust gas emissions were measured on three Ro-Pax vessels sailing in the Adriatic Sea. Testo 350 Maritime exhaust gas analyser was used for monitoring the dry exhaust gas concentrations of CO2 and O2 in percentage, concentrations of CO and NOx in ppm and exhaust gas temperature in °C after the turbocharger at different engine loads. In order to compare and validate measured values, exhaust gas measurement data were also obtained from a Wartsila-Transas simulator model of a similar Ro-Pax vessel during the joint operation of the engine room and navigational simulators. All analysed main engines on three vessels had complete combustion processes in the cylinders with small differences which should be further investigated. Comparison of on board measured parameters with simulated parameters showed that significant fuel oil reduction per voyage could be accomplished by voyage and/or engine operation optimization procedures. Results of this analysis could be used for creating additional emission database and data-driven models for further analysis and improved estimation of exhaust gasses under various marine engine conditions. Additionally, the results could be useful to all interested parties in reducing the fuel oil consumption and emissions of greenhouse and harmful exhaust gases from vessels into the atmosphere. [ABSTRACT FROM AUTHOR]

The paper utilized a panel dataset to investigate the effects of the impact factors, namely, economic growth, energy intensity, energy consumption, urbanisation, passenger vehicles and transport infrastructure investments on carbon emissions (CO2-eq). The transport sector of the main buoyant economic provinces of South Africa for a consecutive period of five years was investigated using STIRPAT models. Carbon emissions coefficient method, (CECM) is made applicable to determine the quantification of the forms of fossil fuels utilized in the transportation sector. The characterized parametric panel dataset for Gauteng, KwaZulu-Natal and Western Cape were assessed from 2016 to 2020 to make objective function determinations. The results indicate that GDP and passenger vehicles contributed largely to CO2-eq emissions, however, the impact varies across the three provinces. Energy intensity and the approach to energy consumption are significant in mitigating carbon emissions, which is due to the possibilities of high fuel efficiency and pollution decrease. The outcome of the research advances climate change mitigation strategy and proffers the required attention to policy makers in South Africa and Africa as a continent.

More than 50% of the world’s population lives in cities. Its buildings consume more than a third of the energy and generate 40% of the emissions. This makes cities in general and their buildings in particular priority points of attention for policymakers and utilities. This paper uses population density as a variable to know its influence on energy consumption and emissions produced in buildings. Furthermore, to show its effect more clearly, the influence of the climate was eliminated. The usual energy consumption in buildings is thermal and electrical. The study was carried out at the city level, both per inhabitant and per household. The area actually occupied by the city was considered. The proposed method was applied to the case of Spanish cities with more than 50,000 inhabitants. The results show that the higher the population density, the higher the energy consumption per inhabitant and household in buildings. The consumption of thermal energy is elastic, while that of electrical energy is inelastic, varying more than 100% between extreme groups. Regarding CO2 emissions, the higher the population density, the higher the emissions. Emissions of electrical origin barely vary by 2% and are greater than those of thermal origin. In addition, the proportion of emissions of electrical origin, with respect to the total, decreases with increasing population density from 74% to 55%. This research aims to help policymakers and utilities to take the appropriate measures that favor the use of renewable energies and reduce CO2 emissions.

This study estimates the relationship between poor indoor environmental quality (IEQ) and the increasing labor costs in green buildings in Taiwan. Specifically, poor performance of IEQ including HVAC, lighting, and indoor air quality, influences the health and well-being of occupants and leads to worse productivity, ultimately causing increased personnel cost. In Taiwan's green building certification (GBC) system, the energy-savings category is mandatory while the IEQ category is only optional. It means that certified building cases may not reach the expected level in IEQ. Thus, this study reviews the thermal environment, indoor air quality (IAQ), and illumination performances of IEQ-certified and non-IEQ-certified buildings in 20 green buildings. Building energy and IEQ simulations were conducted to analyze the relationships between indoor comfort, energy cost, and personnel cost in green buildings. The results show that IEQ-certified green buildings averagely perform better than non-IEQ-certified ones in the aspects of IEQ and building costs. Besides, 3 of 13 non-IEQ-certified green buildings undertake extremely high additional expenditure for the poor IEQ. The results correspond to some previous findings that green-certified buildings do not necessarily guarantee good building performance. This study further inspects the pros and cons of Taiwan's GBC system and proposes recommendations against its insufficient IEQ evaluation category. As the trade-off of energy-saving benefits with health and well-being in green buildings has always been a concern, this study aims to stimulate more quantitative research and promote a more comprehensive green building certification system in Taiwan. [ABSTRACT FROM AUTHOR]

Air filters for general ventilation have mainly been used to control the concentration of indoor particulate matter. In this study, the pressure differential, test dust capacity, quality factor and operating life of class F8 pleat–plate and multi-bag type chemical fiber filters were evaluated using an air filter performance test system. The results showed that the resistance increase rate of multi-bag filter (0.49 Pa/g·(cm/s)) was lower than that of pleat–plate filter (1.94 Pa/g·(cm/s)), the quality factor of the multi-bag filter was lower than that of pleat–plate filter, and the dust capacity of the multi-bag filter was much higher than that of the pleat–plate filter. The operating life of the multi-bag filter was 8 times as that of the pleat–plate filter with the measured PM2.5 of outdoor. The energy consumption of the pleat–plate filter was 2.2 times that of the multi-bag filter. Analyzing the electron microscope photos after dust loading, the dust depth of pleat–plate filter into filter material was thinner than that of multi-bag filter. The research results could provide data support for the design optimization and selection of ventilation filters and the treatment of the particulate matter in indoor environments. [ABSTRACT FROM AUTHOR]

Inland shipping is pivotal to the comprehensive transport system of China. However, ship emission has become a major air polluter in inland river regions, and relevant emission inventories are urgently needed. Currently, the Automatic identification System based (AIS-based)emission model is widely used in calculating the ocean-going ship emission inventory. However, due to the lack of AIS data in the river area, the inland ship emission inventory mainly uses the fuel consumption method. With the continuous improvement of AIS data quality in the river area, the AIS-based emission model can be adopted in the development of inland ship emission inventory. However, there are few studies on the evaluation of the accuracy of the inland ship emissions using the AIS-based emission model. This study makes a comparison between test data and model-calculated data to evaluate the accuracy of the AIS-based emission models. Inland ship activities are divided into being at berth, maneuvering (port departure and port arrival), and on cruise modes in an AIS-based emission model. The model-calculated CO2, HC, and NOx emission rates can cover those onboard emission test data, but the values from the model are much lower. The total average ratios of test data to model-calculated data for CO2, CO, HC, and NOx are 2.66, 19.12, 2.46, and 3.16 when engine loads are below 60%. In upstream cruise mode, average emission rates of CO2, CO, HC, and NOx from the real-world test are 1.91–6.48, 8.78–27.83, 3.05–8.96, and 4.06–5.96 times higher than those from the AIS-based model, respectively. However, those are only 1.08–1.51, 6.74–9.67, 2.03–3.75, and 1.65–2.75 times higher than those from the AIS-based model in downstream cruise mode. [ABSTRACT FROM AUTHOR]

Air pollution has a significant impact on the use of solar energy. On the one hand, the polluted environment directly reduces the intensity of solar radiation, on the other hand, pollution of the environment will also reduce the life of the equipment. Therefore, mastering the dynamic characteristics of the atmospheric environment has certain guiding significance for the efficient utilization of solar energy. In this study, the concentrations of particulate matter, CO, SO2 and NO2 from Tianyun big data website are analyzed to obtain the general characteristics of particulate pollution in Wuhan. At the same time, a long-period sampling atmospheric particulate matter sampler in the Huangjiahu area of Wuhan has been used, and experimental analysis of the physical and chemical characteristics of the samples has been obtained. The results show that both PM2.5 and PM10 show obvious seasonal changes, and the concentration of the four anions during the sampling period is SO42− > NO3− > Cl− > F−. During the sampling period, atmospheric particulate matter is mainly composed of organic matter, inorganic anions and oxides of more than 20 elements. The results of the enrichment factor analysis show that elements such as Br, Pb, Sb and Zn are the main enriched elements during the sampling period. The enrichment factors of these elements are 246.43 ± 168.81, 133.28 ± 115.03, 403.305 ± 396.18 and 90.67 ± 67.01, respectively. The high enrichment of these elements also reflects the contribution of motor vehicle exhaust emission during the sampling period. Traffic source is the main emission source in the Huangjiahu area of Wuhan. This research has a certain guiding significance for many industries such as energy utilization, environmental monitoring, health care, transportation and so on. [ABSTRACT FROM AUTHOR]

The impacts of climate change have severely affected geosphere, biosphere and cryosphere ecosystems in the Hindu Kush Himalayan (HKH) region. The impact has been accelerating further during the last few decades due to rapid increase in anthropogenic activities such as modernization, industrialization and urbanization, along with energy demands. In view of this, the present work attempts to examine aerosol optical depth (AOD) over the HKH region using the long-term homogeneous MERRA-2 reanalysis data from January, 1980 to December, 2020. The AOD trends are examined statistically with student's t-test (t). Due to a vast landmass, fragile topography and harsh climatic conditions, we categorized the HKH region into three sub-regions, namely, the northwestern and Karakoram (HKH1), the Central (HKH2) and the southeastern Himalaya and Tibetan Plateau (HKH3). Among the sub-regions, the significant enhancement of AOD is observed at several potential sites in the HKH2 region, namely, Pokhara, Nainital, Shimla and Dehradun by 55.75 × 10 − 4 ± 3.76 × 10 − 4 , 53.15 × 10 − 4 ± 3.94 × 10 − 4 , 51.53 × 10 − 4 ± 4.99 × 10 − 4 and 39.16 × 10 − 4 ± 4.08 × 10 − 4 AOD year − 1 (550 nm), respectively, with correlation coefficients (Rs) of 0.86 to 0.93. However, at a sub-regional scale, HKH1, HKH2 and HKH3 exhibit 23.33 × 10 − 4 ± 2.28 × 10 − 4 , 32.20 × 10 − 4 ± 2.58 × 10 − 4 and 9.48 × 10 − 4 ± 1.21 × 10 − 4 AOD year − 1 , respectively. The estimated trends are statistically significant (t > 7.0) with R from 0.81 to 0.91. Seasonally, the present study also shows strong positive AOD trends at several potential sites located in the HKH2 region, such as Pokhara, Nainital, Shimla and Dehradun, with minimum 19.81 × 10 − 4 ± 3.38 × 10 − 4 to maximum 72.95 × 10 − 4 ± 4.89 × 10 − 4 AOD year − 1 with statistical significance. In addition, there are also increasing AOD trends at all the high-altitude background sites in all seasons. [ABSTRACT FROM AUTHOR]

An accelerating global energy demand, paired with the harmful environmental effects of fossil fuels, has triggered the search for alternative, renewable energy sources. Biofuels are arguably a potential renewable energy source in the transportation industry as they can be used within current infrastructures and require less technological advances than other renewable alternatives, such as electric vehicles and nuclear power. The literature suggests biofuels can negatively impact food security and production; however, this is dependent on the type of feedstock used in biofuel production. Advanced biofuels, derived from inedible biomass, are heavily favoured but require further research and development to reach their full commercial potential. Replacing fossil fuels by biofuels can substantially reduce particulate matter (PM), carbon monoxide (CO) emissions, but simultaneously increase emissions of nitrogen oxides (NOx), acetaldehyde (CH3CHO) and peroxyacetyl nitrate (PAN), resulting in debates concerning the way biofuels should be implemented. The potential biofuel blends (FT-SPK, HEFA-SPK, ATJ-SPK and HFS-SIP) and their use as an alternative to kerosene-type fuels in the aviation industry have also been assessed. Although these fuels are currently more costly than conventional aviation fuels, possible reduction in production costs has been reported as a potential solution. A preliminary study shows that i-butanol emissions (1.8 Tg/year) as a biofuel can increase ozone levels by up to 6% in the upper troposphere, highlighting a potential climate impact. However, a larger number of studies will be needed to assess the practicalities and associated cost of using the biofuel in existing vehicles, particularly in terms of identifying any modifications to existing engine infrastructure, the impact of biofuel emissions, and their chemistry on the climate and human health, to fully determine their suitability as a potential renewable energy source. [ABSTRACT FROM AUTHOR]

Cities are experiencing a process of suburbanization and last-mile delivery has grown, worsening traffic congestion, pollutant emissions, and citizens' quality of life. Based on a real-life case study, this research compares the environmental performance of different delivery routes carried out by Diesel Light-Duty Vehicles (LDV) according to delivery area, city center or peri-urban. Some 242 delivery routes performed by thirteen drivers were recorded for one month, including instantaneous GPS position, speed, and other parameters (7262 km travelled). Four different delivery routes typologies were compared, and the drag function of the vehicles was characterized. It enabled calibration and modelling dynamics to calculate fuel consumption and pollutant emissions according to delivery routes. The results show that pedestrian crossings, traffic lights, and traffic congestion reduce the average operating speed by up to 57% in the city center and consequently overall energy efficiency. Our results highlight the urgency of replacing diesel LDV for deliveries in the city center with no-motorized transport modes and of implementing intermodality to cover deliveries in residential peri-urban areas. Due to low speeds and frequent start-stops, the efficiency of vehicles in these areas is reduced to a minimum and pollutant emissions increase. The outputs set a basis for recommendations for using LDV only for delivery routes with less traffic interruptions and foster intermodal solutions. [ABSTRACT FROM AUTHOR]