Non-heating Period Research Articles

Граничні можливості централізованого теплопостачання щодо використання електроенергії відновлюваних джерел

The article presents the results of a study on the use of electricity from solar and wind power plants by the centralized heat supply of Ukraine for its direct conversion into heat using electric heat generators (electric boilers and heat pumps). The marginal possibilities of the centralized heat supply of Ukraine regarding the use of this heat energy, which is the purpose of this work, have been assessed. To carry out the analysis, a calculation model was created, limitations were set, and methodical approaches were developed to determine the necessary initial data. Research was conducted for heating and non-heating periods. In the non-heating period, four different options for using electricity from solar and wind power plants for its conversion into heat were simulated. The results of the calculations showed that as of 2021, during the heating period, the demand for thermal energy significantly exceeds the possibilities of its production by electric heat generators that consume electricity from solar and wind power plants. The limit value is the total capacity of solar and wind power plants of 18.514 MW. In the non-heating period, all the electricity produced by solar and wind power plants cannot be fully consumed by electric heat generators of centralized heat supply due to the fact that there will be a surplus of heat energy of 1736.4 thousand MWh. 21.7 million m3 of water will be needed to accumulate this amount of thermal energy with seasonal thermal accumulators. With an average volume of a seasonal heat accumulator of 60,000 m3, you will need about 360 of them. In the conditions of the dense construction of urban settlements, it is unlikely to build such a number of seasonal thermal accumulators. The most likely option is the partial use of electricity from solar and wind power plants by electric heat generators of centralized heating, electrolyzers for hydrogen production and product cooling systems. At the same time, heating boilers on fossil fuel will work together with electric heat generators, which will ensure the reliability of heat supply. Keywords: solar power plants, wind power plants, centralized heat supply, electrothermal generators, electricity.

Research on Remedial Measures Based on the Differences in Atmospheric Particulate Matter Pollution Status between Heating and Non-Heating Periods in Harbin City

Research on Remedial Measures Based on the Differences in Atmospheric Particulate Matter Pollution Status between Heating and Non-Heating Periods in Harbin City

METHODOLOGICAL APPROACHES TO DETERMINING THE GENERAL PARAMETERS OF SOLAR COLLECTORS AND GROUND HEAT ACCUMULATOR FOR A HEAT PUMP HEATING SYSTEM

In this article, the authors considered and described the principle of operation of a combined heat pump heating system of a building consisting of a heat pump, solar collectors and vertical ground heat exchangers. This heat pump system is an energy-efficient and environmentally friendly technology of using renewable energy sources from solar radiation and the ground, which will replace traditional organic fuel for heating the building. An analysis of the direct use of solar energy in heat pump heating systems as a low-potential heat source was carried out and it was found that its effective use in comparison with the natural heat of the ground is limited to the sunny period of the day. It is noted that it is necessary to take into account the difference in climatic conditions, solar insolation and thermal properties of the ground for different regions of the country, which affect the modes of operation and energy efficiency of the heat pump heating system. This heat pump heating system works in combination with solar collectors and a vertical ground heat exchanger in the reverse mode: in the summer, the energy of solar radiation is utilized by solar collectors and with the use of heat exchangers is accumulated in the ground, and in the winter (in the heating period) the accumulated heat is extracted from the ground using a heat pump. The authors conducted an analytical study of the balance energy equations and developed methodological approaches for calculating the required area of solar collectors and the total depth of wells that ensure the functioning of the heating system during the entire heating season, taking into account the influence of the average monthly values of the following factors: temperature coefficient, average heat flux of incident radiation, average the duration of insolation in the non-heating period, the specific heat flow from the ground, the average minimum specific consumption of external electricity for the operation of the electric motors of the heat pump and the circulation pump. The obtained results can be used in the further design development of heat pump heating systems using the renewable energy of the sun and ground for specific residential buildings with given initial data. Bibl. 24, Fig. 3, Tab. 4.

Characteristics and health risks assessment of PM2.5-bound heavy metals during winter in urban areas of northern China: A case study in Kaifeng

Characteristics and health risks assessment of PM2.5-bound heavy metals during winter in urban areas of northern China: A case study in Kaifeng

Pollution Characteristics and Source Apportionment of Volatile Organic Compounds in Typical Solvent-using Industrial Parks in Beijing

The BCT-7800A PLUS VOC online monitor system was employed to measure ambient volatile organic compounds （VOCs） in a typical solvent-using industrial park in Beijing. From January to June 2023, the pollution characteristics, source apportionment, and ozone formation potential（OFP）of VOCs were studied, and the results of a comparative analysis were also discussed between heating and non-heating periods. The results indicated that VOC concentrations from January to June 2023 were （104.21 ± 91.31） μg·m-3 on average. The concentrations of TVOCs under the influence of southerly and northerly winds were （214.18 ± 202.37） μg·m-3 and （197.56 ± 188.3） μg·m-3, respectively. Alkanes were the species with the highest average concentration and proportion, respectively （45.53 ± 41.43） μg·m-3. The VOC concentration during the heating period was higher than those during the non-heating period, with values of （111.57 ± 83.96） μg·m-3 and （87.92 ± 75.03） μg·m-3, respectively. Propane and ethane were the species with the highest average concentration during the heating period. Compared with those in the non-heating period, the average concentrations of three species （propane, ethane, and n-butane） in the top ten species increased during the heating period, with average concentrations increasing by 51.94%, 54.64%, and 26.32%, respectively. The source apportionment results based on the positive matrix factorization （PMF） model indicated that the major sources of VOCs in the park during the monitoring period were printing emission sources （4.95%）, oil and gas evaporation sources （9.52%）, fuel combustion sources （15.44%）, traffic emissions sources （18.97%）, electronic equipment manufacturing （24.59%）, and industrial painting sources （26.52%）. Therefore, industrial painting sources, electronic equipment manufacturing sources, and traffic emissions sources were the emission sources that the park should focus on controlling. Compared with those during non-heating periods； industrial painting, traffic emission, and fuel combustion sources contributed more during the heating period, with VOC concentrations increasing by 15.02%, 16.53%, and 24.98%, respectively. The average OFP of VOCs from May to June during the monitoring period was 198.51 μg·m-3 and OVOCs, olefins, and aromatic hydrocarbons contributed the most to OFP, which were 47.41%, 22.15%, and 18.41%, respectively. The electronic equipment manufacturing source was the largest contributor to the summer OFP of the park and its contribution rate was 30.11%, which should be strengthened in the future.

Variations of black carbon, particulate matter and nitrogen oxides mass concentrations in urban environment with respect to winter heating period and meteorological conditions

The atmospheric concentrations of particulate pollution are of great scientific concern due to their impact on both human health and environment. This study aimed to investigate the concentration of black carbon (BC), particulate matter with an aerodynamic diameter of less than 10 micrometres (PM10) and nitrogen oxides (NOx) at an urban background environment throughout the year, and understand the impact of winter heating and meteorology on its concentration level. The campaign covered heating and non-heating periods, from 1 June 2021 to 31 May 2022. During the heating period, the mass concentrations of BC, PM10 and NOx were 1.17, 24.9 and 19.4 µg m–3, respectively. The analysis revealed that the mass concentrations of BC and NOx were 1.9 and 1.4 times greater during the heating period, respectively, compared to the non-heating period. In contrast, PM10 remained almost constant during the heating (19.4 µg m–3) and non-heating periods (20.0 µg m–3). Throughout the year, the BC mass concentration was dominated by BCFF (71.2%) originating from fossil fuel combustion with a maximum (8.43 µg m–3) during the heating period. Moreover, wind speed presented a weak negative correlation with BC (r = –0.40), PM10 (r = –0.19) and NOx (r = –0.40) during the heating period.

Optimization and simulation of a novel multi-energy complementary heat pump system in cold regions

Optimization and simulation of a novel multi-energy complementary heat pump system in cold regions

Prediction models for building thermal mass of intermittently heated rooms for balancing energy consumption and indoor thermal comfort

Prediction models for building thermal mass of intermittently heated rooms for balancing energy consumption and indoor thermal comfort

Analysis of the synergistic benefits of typical technologies for pollution reduction and carbon reduction in the iron and steel industry in the Beijing–Tianjin–Hebei region

With its high energy consumption and pollutant emissions, the iron and steel industry is a significant source of air pollution and carbon emissions in the Beijing–Tianjin–Hebei (BTH) region. To improve air quality and reduce greenhouse gas emissions, a series of policies involving ultra-low emission, synergistic reduction of pollution, and carbon application have been implemented in the region. This study has assessed air pollutant and CO2 emission patterns in the iron and steel industry of the region by employing co-control effects coordinate system, marginal abatement cost curve, and numerical modeling, along with the synergistic benefits of typical technologies. The results have demonstrated that: (1) the intensive production activities pertinent to iron and steel enterprises has contributed greatly to the emission in Tangshan and Handan, where the sintering process is the main source of SO2, NOx, PM2.5, and CO, accounting for 64.86%, 55.15%, 29.98%, and 46.43% of the total emissions, respectively. (2) Among the typical pollution control and reduction measures, industrial restructuring and adjustment of the energy-resource structure have led to the greatest effects on emission reduction. Technologies exhibiting great potential in emission reduction and high-cost efficiency such as Blast Furnace Top Gas Recovery Turbine Unit (TRT) need to be promoted. (3) In Tangshan city with the highest level of steel production, the iron and steel production activities contributed to the concentration of 30.51% of PM2.5, 50.67% of SO2, and 42.54% of NO2 during the non-heating period. During the heating period, pollutants pertinent to the combustion of fossil energy for heating have increased, while iron and steel induced emissions have decreased to 23.7%, 34.32%, and 29.13%, respectively. By 2030, it is speculated that the contribution of the iron and steel industry to air quality will be significantly decreased as result of successful implementation of ultra-low emission policies and typical synergistic reduction technologies.

Particulate black carbon mass concentrations and the episodic source identification driven by atmospheric blocking effects in Astana, Kazakhstan

Particulate black carbon mass concentrations and the episodic source identification driven by atmospheric blocking effects in Astana, Kazakhstan

Apportioning and Locating PM2.5 Sources Affecting Coastal Cities: Ulsan in South Korea and Dalian in China

PM2.5 mass and its constituent species were analyzed in two coastal cities (Ulsan, South Korea, and Dalian, China) between July 13, 2018, and September 20, 2019. Ten and nine sources were identified in Ulsan and Dalian, respectively, using positive matrix factorization (PMF). In Ulsan, three sources (secondary nitrate [SN], secondary sulfate [SS], and traffic) contributed ~83.0% of the PM2.5 mass concentration (23.7 µg m–3) during the heating period. In Dalian, four sources (SN, SS, traffic, and residential burning) accounted for ~84.3% of the total PM2.5 mass concentration (47.8 µg m–3). Higher contributions of residential burning in Dalian (11.7 µg m–3) than biomass burning in Ulsan (0.22 µg m–3) were resolved during the heating period as was a higher proportion of SS contributions in Ulsan (6.28 µg m–3, 41.6%) than in Dalian (6.42 µg m–3, 21.2%) during non-heating period. Squared correlation coefficients (r2) of sources common to the two cities were examined for lag times from –2 days to +4 days from Dalian to Ulsan. The largest r2 of PM2.5 mass concentrations during the heating period was 0.34 on Lag day 1. The same day, largest r2 during the non-heating period was 0.14 indicating, stronger, lagged PM2.5 correlations during the heating period. The SN, SS, soil, and oil combustion sources, with r2 values of 0.25, 0.20, 0.41, and 0.25, respectively, show fair correlations between the cities for these sources during the heating period. Probable source locations were identified by simplified quantitative transport bias analysis (SQTBA) and potential source contribution function (PSCF) as a multiple site approach and a single site approach, respectively. Weaker correlations of SN (r2 = 0.15) and SS (r2 < 0.1) during the non-heating period were supported by the different probable source locations. This study identified the sources requiring individual national and/or joint international efforts to reduce ambient PM2.5 in these neighboring countries.

Sources and formation of fine particles and organic aerosols during autumn-winter period in the southern edge of northern China plain

Sources and formation of fine particles and organic aerosols during autumn-winter period in the southern edge of northern China plain

Pollution characteristics, source apportionment and absorption spectra of size-resolved PAHs in atmospheric particles in a cold megacity of China

Pollution characteristics, source apportionment and absorption spectra of size-resolved PAHs in atmospheric particles in a cold megacity of China

Influence of heat storage on performance of multi-borehole mid-deep borehole heat exchangers

Influence of heat storage on performance of multi-borehole mid-deep borehole heat exchangers

Small-scale district heating system as heat storage for decentralized solar thermal collectors during non-heating period

Small-scale district heating system as heat storage for decentralized solar thermal collectors during non-heating period

Environmental impact assessment of the coal yard and ambient pollution.

This study investigates the vertical distribution of pollutants emitted from coal yards using unmanned aerial vehicles (UAVs). Vertical concentration measurements of black carbon (BC) and particulate matter (PM) inarange of 1m to 100m above ground level (AGL) in the central coal yard showed clear spatial patterns and gradients of these pollutants. In addition, measurements were taken at specific heights (1 m, 30 m AGL, and60mAGL) at seven locations approximately 3 km from the yard. Thirteen measurements were carried out during the non-heating period under similar weather conditions. The measured BC concentrations decreased significantly with increasing altitude, with ground-level concentrations reaching 1.88 ± 0.61µg/m3 and decreasing by over 46% at 80 m AGL. Similarly, PM10 concentrations at 60 m AGL decreased by 21.7%, with values of25.99 ± 9.24µg/m3 measured near the ground level and 16.52 ± 8.31µg/m3 at 60 m AGL. The maximum coal particle pollution from the coal depot ranges from 500 to 1,000 m. The study showed a significant decrease in BC concentrations with height above the coal yard surface. Concentrations of PM10 and PM10-TSP showed a complex distribution influenced by local emissions and long-range particle transport. Meteorological factors, especially wind speed and direction, significantly influenced the pollutant dispersion. In addition, higher pollutant concentrations were measured during dry periods than after rainfall. The findings of this study contribute to abetter understanding of the dispersion patterns and potential impacts of coal dust, enabling the implementation of targeted mitigation strategies and improved pollution control measures.

Investigation of Indoor Airborne Bacteria in the Severe Cold Region in China: Genera, Levels, and the Influencing Factors of Concentration

In regions experiencing severe cold, inadequate ventilation during winter months often leads to increased concentrations of indoor pollutants. While there have been several studies on indoor particulate matter and inorganic pollutants in such regions, bioaerosol pollution has not been as extensively investigated. This study examines the indoor bioaerosol situation in a university located in one of the severe cold regions in China, focusing on bacteria as a representative pollutant. It investigated random samples of an office and a dormitory (including washrooms) and spanned heating and nonheating periods. The findings indicated that bacterial abundance in the dormitory and office was approximately equivalent. The predominant airborne bacterial communities identified were Proteobacteria, Bacteroidota, Actinobacteriota, Firmicutes, and Myxococcota. Opening windows effectively reduced bacterial concentrations during both heating and nonheating periods. When windows remained closed, bacterial concentrations exceeded the standard by 9.1% during the nonheating period and by 14.3% during the heating period. Furthermore, temperature and relative humidity influenced bacterial particle size, activity, and consequently, aerosol concentrations. In the office, the highest percentage of bioaerosols was observed in particle sizes &lt;1.1 and 1.1–2.1 μm, with smaller percentages observed in other particle sizes. Conversely, the percentage of particle sizes 2.1–3.3 μm in the dormitory was higher. The highest bacterial aerosol concentrations were detected in the morning in both the dormitory and office, during heating and nonheating periods. Bacterial concentrations in the office were lower on weekends than on weekdays, whereas in the dormitory, concentrations were higher on weekends than on weekdays. The above results indicate that indoor bacterial aerosol pollution is serious in winter in severe cold regions, which needs more attention.

Machine learning revealing key factors influencing HONO chemistry in Beijing during heating and non-heating periods

Machine learning revealing key factors influencing HONO chemistry in Beijing during heating and non-heating periods

Oxidative potential in rural, suburban and city centre atmospheric environments in central Europe

Abstract. Oxidative potential (OP) is an emerging health-related metric which integrates several physicochemical properties of particulate matter (PM) that are involved in the pathogenesis of the diseases resulting from exposure to PM. Daily PM2.5-fraction aerosol samples collected in the rural background of the Carpathian Basin and in the suburban area and centre of its largest city of Budapest in each season over 1 year were utilised to study the OP at the related locations for the first time. The samples were analysed for particulate matter mass, main carbonaceous species, levoglucosan and 20 chemical elements. The resulting data sets were subjected to positive matrix factorisation to derive the main aerosol sources. Biomass burning (BB), suspended dust, road traffic, oil combustion mixed with coal combustion and long-range transport, vehicle metal wear, and mixed industrial sources were identified. The OP of the sample extracts in simulated lung fluid was determined by ascorbic acid (AA) and dithiothreitol (DTT) assays. The comparison of the OP data sets revealed some differences in the sensitivities of the assays. In the heating period, both the OP and PM mass levels were higher than in spring and summer, but there was a clear misalignment between them. In addition, the heating period : non-heating period OP ratios in the urban locations were larger than for the rural background by factors of 2–4. The OP data sets were attributed to the main aerosol sources using multiple linear regression with the weighted least squares approach. The OP was unambiguously dominated by BB at all sampling locations in winter and autumn. The joint effects of motor vehicles involving the road traffic and vehicle metal wear played the most important role in summer and spring, with considerable contributions from oil combustion and resuspended dust. In winter, there is temporal coincidence between the most severe daily PM health limit exceedances in the whole Carpathian Basin and the chemical PM composition causing larger OP. Similarly, in spring and summer, there is a spatial coincidence in Budapest between the urban hotspots of OP-active aerosol constituents from traffic and the high population density in central quarters. These features offer possibilities for more efficient season-specific air quality regulations focusing on well-selected aerosol sources or experimentally determined OP, rather than on PM mass in general.

Soil-Derived Dust PM10 and PM2.5 Fractions in Southern Xinjiang, China, Using an Artificial Neural Network Model

Soil-derived dust emissions have been widely associated with health and environmental problems and should therefore be accurately and reliably estimated and assessed. Of these emissions, the inhalable PM10 and PM2.5 are difficult to estimate. Consequently, to calculate PM10 and PM2.5 emissions from soil erosion, an approach based on an artificial neural network (ANN) model which provides a multilayered, fully connected framework that relates input parameters and outcomes was proposed in this study. Owing to the difficulty in obtaining the actual emissions of soil-derived PM10 and PM2.5 over a broad area, the PM10 and PM2.5 simulated results of the ANN model were compared with the published results simulated by the widely used wind erosion prediction system (WEPS) model. The PM10 and PM2.5 emission results, based on the WEPS, agreed well with the field data, with R2 values of 0.93 and 0.97, respectively, indicating the potential for using the WEPS results as a reference for training the ANN model. The calculated r, RMSE and MAE for the results simulated by the WEPS and ANN were 0.78, 3.37 and 2.31 for PM10 and 0.79, 1.40 and 0.91 for PM2.5, respectively, throughout Southern Xinjiang. The uncertainty of the soil-derived PM10 and PM2.5 emissions at a 95% CI was (−66–106%) and (−75–108%), respectively, in 2016. The results indicated that by using parameters that affect soil erodibility, including the soil pH, soil cation exchange capacity, soil organic content, soil calcium carbonate, wind speed, precipitation and elevation as input factors, the ANN model could simulate soil-derived particle emissions in Southern Xinjiang. The results showed that when the study domain was reduced from the entire Southern Xinjiang region to its five administrative divisions, the performance of the ANN improved, producing average correlation coefficients of 0.88 and 0.87, respectively, for PM10 and PM2.5. The performances of the ANN differed by study period, with the best result obtained during the sand period (March to May) followed by the nonheating (June to October) and heating periods (November to February). Wind speed, precipitation and soil calcium carbonate were the predominant input factors affecting particle emissions from wind erosion sources. The results of this study can be used as a reference for the wind erosion prevention and soil conservation plans in Southern Xinjiang.