Average Temperature Research Articles

Warming effects on grassland soil microbial communities are amplified in cool months.

Global warming modulates soil respiration (RS) via microbial decomposition, which is seasonally dependent. Yet, the magnitude and direction of this modulation remain unclear, partly owing to the lack of knowledge on how microorganisms respond to seasonal changes. Here, we investigated the temporal dynamics of soil microbial communities over 12 consecutive months under experimental warming in a tallgrass prairie ecosystem. The interplay between warming and time altered (p < 0.05) the taxonomic and functional compositions of microbial communities. During the cool months (January to February and October to December), warming induced a soil microbiome with a higher genomic potential for carbon decomposition, community-level ribosomal RNA operon (rrn) copy numbers, and microbial metabolic quotients, suggesting that warming stimulated fast-growing microorganisms that enhanced carbon decomposition. Modeling analyses further showed that warming reduced the temperature sensitivity of microbial carbon use efficiency (CUE) by 28.7% when monthly average temperature was low, resulting in lower microbial CUE and higher heterotrophic respiration (Rh) potentials. Structural equation modeling showed that warming modulated both Rh and RS directly by altering soil temperature and indirectly by influencing microbial community traits, soil moisture, nitrate content, soil pH, and gross primary productivity. The modulation of Rh by warming was more pronounced in cooler months compared to warmer ones. Together, our findings reveal distinct warming-induced effects on microbial functional traits in cool months, challenging the norm of soil sampling only in the peak growing season, and advancing our mechanistic understanding of the seasonal pattern of RS and Rh sensitivity to warming.

Entomophagy: A sustainable food alternative to save planet

Climate change not only fringes rising average temperatures but shifting wildlife populations, rising seas, extreme weather events and other impacts. These changes are due to addition of greenhouse gases to the atmosphere due to impact of human activities. One of the important human activities which are a major contributor of greenhouse gas is Animal Agriculture. Meat consumption is responsible for releasing greenhouse gases such as methane, CO, and nitrous oxide. Livestock production accounts for 14.5% of all anthropogenic greenhouse gas emissions, with beef having the highest footprint due to large amounts of methane that an average cow produces. Agriculture accounts for 92% of the freshwater footprint of humanity; almost 35% relates to animal farming. The production of meat is directly and indirectly related to the loss of forests in South America, Amazon Rainforest and other areas of Brazil, Argentina and Paraguay. And many species face extinction or are under threat due to the destruction of natural environments. Sustainable alternative to going meat-free is entomophagy or insect farming which produces about 100 times less greenhouse gases per kg of mass organism gain. Edible insects like grasshoppers, crickets and mealworms are rich in protein and contain significantly higher sources of minerals such as iron, zinc, copper, and magnesium than beef. Regardless of its environmental benefits, entomophagy comes with its unique set of challenges.

Influence of hydrometeorological risk factors on child diarrhea and enteropathogens in rural Bangladesh.

A number of studies have detected relationships between weather and diarrhea. Few have investigated associations with specific enteric pathogens. Understanding pathogen-specific relationships with weather is crucial to inform public health in low-resource settings that are especially vulnerable to climate change. Our objectives were to identify weather and environmental risk factors associated with diarrhea and enteropathogen prevalence in young children in rural Bangladesh, a population with high diarrheal disease burden and vulnerability to weather shifts under climate change. We matched temperature, precipitation, surface water, and humidity data to observational longitudinal data from a cluster-randomized trial that measured diarrhea and enteropathogen prevalence in children 6 months-5.5 years from 2012-2016. We fit generalized additive mixed models with cubic regression splines and restricted maximum likelihood estimation for smoothing parameters. Comparing weeks with 30°C versus 15°C average temperature, prevalence was 3.5% higher for diarrhea, 7.3% higher for Shiga toxin-producing Escherichia coli (STEC), 17.3% higher for enterotoxigenic E. coli (ETEC), and 8.0% higher for Cryptosporidium. Above-median weekly precipitation (median: 13mm; range: 0-396mm) was associated with 29% higher diarrhea (adjusted prevalence ratio 1.29, 95% CI 1.07, 1.55); higher Cryptosporidium, ETEC, STEC, Shigella, Campylobacter, Aeromonas, and adenovirus 40/41; and lower Giardia, sapovirus, and norovirus prevalence. Other associations were weak or null. Higher temperatures and precipitation were associated with higher prevalence of diarrhea and multiple enteropathogens; higher precipitation was associated with lower prevalence of some enteric viruses. Our findings emphasize the heterogeneity of the relationships between hydrometeorological variables and specific enteropathogens, which can be masked when looking at composite measures like all-cause diarrhea. Our results suggest that preventive interventions targeted to reduce enteropathogens just before and during the rainy season may more effectively reduce child diarrhea and enteric pathogen carriage in rural Bangladesh and in settings with similar meteorological characteristics, infrastructure, and enteropathogen transmission.

Hydrogen, medium-range airplane design optimization for minimal global warming impact

AbstractThis paper focuses on the conceptual design optimization of liquid hydrogen aircraft and their performance in terms of climate impact, cash operating cost, and energy consumption. An automated, multidisciplinary design framework for kerosene-powered aircraft is extended to design liquid hydrogen-powered aircraft at a conceptual level. A hydrogen tank is integrated into the aft section of the fuselage, increasing the operating empty mass and wetted area. Furthermore, the gas model of the engine is adapted to account for the hydrogen combustion products. It is concluded that for medium-range, narrow-body aircraft using hydrogen technology, the climate impact can be minimized by flying at an altitude of 6.0 km at which contrails are eliminated and the impact due to $$\hbox {NO}_{\textrm{x}}$$ NO x emissions is expected to be small. However, this leads to a deteriorated cruise performance in terms of energy and operating cost due to the lower lift-to-drag ratio (– 11%) and lower engine overall efficiency (– 10%) compared to the energy-optimal solutions. Compared to cost-optimal kerosene aircraft, the average temperature response can be reduced by 73–99% by employing liquid hydrogen, depending on the design objective. However, this reduction in climate impact leads to an increase in cash operating cost of 28–39% when considering 2030 hydrogen price estimates. Nevertheless, an analysis of future kerosene and hydrogen prices shows that this cost difference can be significantly decreased beyond 2030.

Heat Characteristics and Emission Effect of a Fuel-operated Auxiliary Air Heater Fed with Fuel E10, E30 and E100

In order to increase the comfort of vehicle passengers in specific vehicle categories, the heating of the passenger compartment is not provided by the heat from the engine driving the vehicle but by an additional heating device. The study examines the effect of auxiliary heaters that use liquid fuels to heat the passenger compartment of vehicles. The device was operated during the test with two different mixtures containing bioethanol (E30, E100) and the original motor gasoline (E10). It aimed to understand the effects of different fuels, particularly heating performance, operating time and emissions. Based on the results, as the ethanol content increases, the temperature of the device’s flame and heating air decreases. The experiments showed that in the case of E100 bioethanol, the average temperature measured in stable operating conditions was significantly lower than in the case of E10 motor gasoline. That suggests that an increase in the ethanol content reduces the heating performance. Another significant result of the study was that in the case of mixtures containing ethanol, a longer operating time is required to achieve the same amount of heat, which leads to additional fuel consumption. In addition, when using E100 bioethanol, the amount of harmful gases that are emitted increases significantly during the longer operating time. This observation can be important for evaluating the environmental impact and efficiency of vehicles.

Case study: reducing heating energy consumption in a high tunnel greenhouse with renewable energy and microclimate control by bench-top root-zone heating, bench covers, and under-bench insulation

Appalachian State University's Nexus project designed an efficient greenhouse heating system that integrated renewable energy and root zone heating technology to reduce the greenhouse heating energy burden on local farmers and installed it at local cooperative farms. This study analyzed 5 years of data from 2018 to 2022 to investigate the energy savings and microclimate control effectiveness of the Nexus heating system installed at Springhouse Farm in North Carolina, USA. By varying bench cover materials, bottom insulation, and the number of loops of root zone tubing, the different soil temperatures required for plant types and growth stages were achieved with a single temperature controller. A root zone heating fluid of 32.2 ℃ satisfactorily maintained the germination soil between 20 and 25 ℃ in March 2019 with an average outside temperature of 4.8 ℃ and an average low temperature of − 0.4 ℃. Growing soil maintained an average temperature of 15 ℃ with bottom insulation and an average of 11–12 ℃ without bottom insulation. Compared to the conventional heating system (a forced-air propane unit heater alone), weather-adjusted propane consumption (propane usage divided by heating degree days) was reduced by 65% with the Nexus system alone and 45% with the Nexus system and unit heater together. It shows that the Nexus system has significantly reduced greenhouse heating energy consumption and maintained productive conditions. The renewable energy fraction ranged only 9–13% of the total thermal energy used due to the high inlet temperature entering the solar thermal collector. This can be improved by separating the heat storage and backup heat source.

Using Transfer Learning and XGBoost for Early Detection of Fires in Offshore Wind Turbine Units

To improve the power generation efficiency of offshore wind turbines and address the problem of high fire monitoring and warning costs, we propose a data-driven fire warning method based on transfer learning for wind turbines in this paper. This paper processes wind turbine operation data in a SCADA system. It uses an extreme gradient-boosting tree (XGBoost) algorithm to build an offshore wind turbine unit fire warning model with a multiparameter prediction function. This paper selects some parameters from the dataset as input variables for the model, with average cabin temperature, average outdoor temperature, average cabin humidity, and average atmospheric humidity as output variables. This paper analyzes the distribution information of input and output variables and their correlation, analyzes the predicted difference, and then provides an early warning for wind turbine fires. This paper uses this fire warning model to transfer learning to different models of offshore wind turbines in the same wind farm to achieve fire warning. The experimental results show that the prediction performance of the multiparameter is accurate, with an average MAPE of 0.016 and an average RMSE of 0.795. It is better than the average MAPE (0.051) and the average RMSE (2.020) of the prediction performance of a backpropagation (BP) neural network, as well as the average MAPE (0.030) and the average RMSE (1.301) of the prediction performance of random forest. The transfer learning model has good prediction performance, with an average MAPE of 0.022 and an average RMSE of 1.469.

Climate model selection via conformal clustering of spatial functional data

AbstractClimate model selection stands as a critical process in climate science and research. It involves choosing the most appropriate climate models to address specific research questions, simulating climate behaviour, or making projections about future climate conditions. This paper proposes a new approach, using spatial functional data analysis, to asses which of the 18 EURO CORDEX simulation models work better for predicting average temperatures in the Campania region (Italy). The method involves two key steps: first, using functional data analysis to process climate variables and select optimal models by a hierarchical clustering procedure; second, validating the chosen models by proposing a new conformal prediction approach to the anomalies associated to each cluster.

Effect of Climate Change on Nigerian Economic Sustainability

Climate change is seen as a statistical variation that persists for an extended period, frequently for as long as a decade or more. Moreover, the issue of climate change which has gained global attention poses a serious threat to developing economy like Nigeria, which is characterized by widespread poverty as a result of economic instability. It is against this backdrop that this research is aimed at investigating the effect of climate change on Nigerian economic sustainability. The research made use of Autoregressive Distributive Lag (ARDL)/bond test approach and OLS estimation technique, while data for the period of 1990-2020 was collected. Changes in average temperature and carbon emission were used to capture climate change, while variation in exchange rate and agricultural production were used as control variables. The result of the analysis showed that the goodness-of-fit (R-Square) is 0.998. This means that 99.8% of the changes in the dependent variable (GDP) can be explained by the changes in the independent variables (CEM, AGRIC, EXR, TEMP). The annual speed of adjustment from short run to long run relationship is 34%. At F-statistic = 195.8052 and P value = 0.000, the model is statistically significant at 1% level. The results of the analysis further demonstrated that both in long-run and short-run, carbon emissions adversely affect Nigerian economic sustainability. Additionally, average atmospheric temperature was significantly related to sustainability of Nigerian economy in the short run. It was concluded that environmental stakeholders as well as Nigerian government should develop and enforce policies to reduce carbon emissions and forest depletion. Also, efforts should be made by government towards ensuring that policies that are environmentally friendly are made that can encourage agricultural production in order to reduce import of agricultural produce, thereby boosting economic growth.

A Comparative Study on Coupled Fluid–Thermal Field of a Large Nuclear Turbine Generator with Radial and Composited Radial–Axial–Radial Ventilation Systems

With the continuous growth of energy demand, the advantages of nuclear power, such as high energy density, low emissions, and cleanliness, are gradually highlighted. However, the increasing capacity of the turbine generator in nuclear power plants has led to greater losses and critical heating issues. Designing an effective cooling system plays an important role in improving the rotor’s heat dissipation ability, especially under the condition of limited rotor space. In this study, the cooling effects of the rotor using a radial straight-type cooling structure and a composited radial–axial–radial cooling structure are compared and analyzed for a 1555 MVA hydrogen-cooled nuclear turbine generator. Three-dimensional fluid thermal coupled models of the rotor with both cooling structures are established, and corresponding boundary conditions are provided. The models are solved using the finite volume method. The flow law of cooling hydrogen gas inside the rotor and the temperature distribution of various parts of the rotor are studied in detail. Compared with the radial straight-type cooling structure, adopting the composited radial–axial–radial cooling structure can reduce the average temperature of the rotor field windings by 4.5 °C. The research results provide a reference for the design and optimization of the rotor cooling system for large-capacity nuclear turbine generators.

Alternative climate metrics to the Global Warming Potential are more suitable for assessing aviation non-CO2 effects

A growing body of research has highlighted the major contribution of aviation non-CO2 emissions and effects to anthropogenic climate change. Regulation of these emissions, for example in the EU Emissions Trading System, requires the use of a climate metric. However, choosing a suitable climate metric is challenging due to the high uncertainties of aviation non-CO2 climate impacts, their variability in atmospheric lifetimes and their dependence on emission location and altitude. Here we use AirClim to explore alternatives to the conventional Global Warming Potential (GWP) by analysing the neutrality, temporal stability, compatibility and simplicity of existing climate metrics and perform a trade-off. We find that using the temperature-based Average Temperature Response (ATR) or using an Efficacy-weighted GWP (EGWP) would enable a more accurate assessment of existing as well as future aircraft powered by novel aviation fuels.

A long-term study on the impact of climatic variables on two common nest-dwelling ectoparasites of the Eurasian blue tit (Cyanistes caeruleus).

We explored the potential influence of temperature and precipitation on the abundance of two nest-dwelling ectoparasites (blowflies and mites) of Eurasian blue tits (Cyanistes caeruleus) during a period of 21 years and compared the results with those of a shorter period. The abundance of blowflies was negatively related to precipitation, which could prevent flies from locating their host, and laying date. In addition, blowflies were positively related to brood size (more food implies more parasites) and the interaction between precipitation and temperature. The highest abundances of blowfly pupae were attained in conditions of increasing precipitation and decreasing temperature, which should be more common at the beginning of the bird breeding season. Mites were significantly and positively related to laying date and the interaction between average precipitation and temperature but only for the larger dataset. Higher abundances of mites were related to intermediate values of temperature and precipitations, conditions that are found at the end of the breeding season. These results imply that optimal conditions for both parasites differ, with blowflies preferring earlier breeders and colder and more humid conditions than mites. Thus, the effects of the climatic conditions studied on parasite abundances are non-monotonic and can vary with years and parasite species. Finally, the fact that average temperature and precipitation decreases across the years of study is probably due to the advancement in Eurasian blue tit laying date because we calculated those variables for the period of birds' reproduction. This earlier nesting does not affect parasite abundance.

Impact of Climate Change on the Farming Community of Bhaktapur District of Nepal

This study was carried out to evaluate the impact of climate change on the farming community in Bhaktapur, Nepal. The study considered rainfall, temperature, flood/drought, harvest and sowing time, and pest and disease incidence over 20 years as primary factors to be considered. A household survey of 120 houses was conducted following the set of questionnaires prepared. As a result, significant changes were observed in climatic aspects as well as biological aspects. The obtained result demonstrated that the precipitation observed drastic change as there was an incidence of erratic and heavy rainfall on summer days while the intensity and frequency of rainfall decreased during winter. These abnormalities certainly do not favor agriculture and farming. Similarly, the temperature of the study area has increased annually over the last two decades. The data suggests that the average annual temperature is increasing at the rate of 0.038°C per year. Moreover, the survey showed that the time of harvest and time of sowing seeds have been delayed respectively to the time a few decades back while the climatic aberrations have increased the incidence of pests and diseases. In a nutshell, the changes in climatic conditions have a drastic change in the farming system and thus the agricultural produce and productivity. The study highlights the significant impact of climate change on traditional farming practices in Bhaktapur, Nepal. It underscores how changes in rainfall patterns, temperature, and the incidence of extreme weather events like floods and droughts have disrupted agricultural activities such as planting and harvesting cycles. The research not only identifies challenges but also emphasizes the need for adaptation strategies to mitigate the impacts of climate change on farming communities. By linking research findings to policy recommendations and practical interventions, the study offers actionable insights for policymakers, practitioners, and local stakeholders striving to build resilience in agricultural systems.

Printed Thick Film Resistance Temperature Detector for Real-Time Tube Furnace Temperature Monitoring

Accurately acquiring crucial data on tube furnaces and real-time temperature monitoring of different temperature zones is vital for material synthesis technology in production. However, it is difficult to achieve real-time monitoring of the temperature field of tube furnaces with existing technology. Here, we proposed a method to fabricate silver (Ag) resistance temperature detectors (RTDs) based on a blade-coating process directly on the surface of a quartz ring, which enables precise positioning and real-time temperature monitoring of tube furnaces within 100–600 °C range. The Ag RTDs exhibited outstanding electrical properties, featuring a temperature coefficient of resistance (TCR) of 2854 ppm/°C, an accuracy of 1.8% FS (full scale), and a resistance drift rate of 0.05%/h over 6 h at 600 °C. These features ensured accurate and stable temperature measurement at high temperatures. For demonstration purposes, an array comprising four Ag RTDs was installed in a tube furnace. The measured average temperature gradient in the central region of the tube furnace was 5.7 °C/mm. Furthermore, successful real-time monitoring of temperature during the alloy sintering process revealed approximately a 20-fold difference in resistivity for silver-palladium alloys sintered at various positions within the tubular furnace. The proposed strategy offers a promising approach for real-time temperature monitoring of tube furnaces.

Investigating the relationship between heat load and shade seeking behaviour in dairy buffaloes.

The study presented in this Research Communication aimed to investigate the relationship between physiological responses, body surface temperature and shade-seeking behaviour in Nili Ravi dairy buffaloes during summer months. We enrolled 60 buffaloes, and each animal was observed for three consecutive days starting before sunrise until they moved towards the shade structures. A repeated measures ANOVA was employed to assess the changes in physiological parameters and body surface temperature between the early morning and the occurrence of shade-seeking behaviour. The average temperature humidity index and heat load index during the behavioural monitoring period (0400 to 1200 h) were 81.3 ± 6.5 and 92.9 ± 17, respectively (mean ± sd). There was no significant difference in core body temperature between sunrise and the time of shade-seeking event. However, the buffaloes had a slightly higher respiration rate at the time of shade-seeking (19.2 vs. 22.4 breaths/min). In addition, body surface temperature, measured at the flank region, shoulder, base of the ear and forehead was significantly higher at the occurrence of shade-seeking behaviour compared to the early morning. On average, the buffaloes sought shade when the surface temperature was 2°C higher than the temperature recorded before sunrise. Overall, the current findings suggest that body surface temperature, rather than core body temperature was strongly associated with shade-seeking behaviour in dairy buffaloes. These findings could be useful in developing strategies to mitigate the effects of heat stress in dairy buffalo herds and thereby improve animal welfare.

A 1.65‐nW 11.14‐ppm/°C self‐biased subthreshold CMOS voltage reference with temperature compensation circuit

SummaryThis paper presents a subthreshold CMOS voltage reference (VR) that utilizes self‐biased circuits. This voltage reference includes temperature compensation circuits to expand its operating temperature range and reduce its temperature coefficient. The proposed CMOS voltage reference is designed using a standard 0.18‐μm CMOS process and has a small area of only 0.005 mm2. Post‐layout simulation results demonstrate that the power consumption of the circuit at room temperature (25°C) is only 1.65 nW at a power supply voltage of 1 V. In this case, the voltage reference output is 316.56 mV, with an average temperature coefficient (TC) of 11.14 ppm/°C in a wide temperature range from −40°C to 140°C. Furthermore, the line sensitivity (LS) of the circuit is 0.024%/V, and the power supply rejection ratio (PSRR) of the circuit is −86.5 dB at 10 Hz. In summary, the subthreshold CMOS voltage reference structure proposed in this paper demonstrates excellent performance characteristics, such as low power consumption, a small area, and high‐temperature stability. These features make it a promising candidate for voltage reference for low‐power applications with significant changes in environmental temperature.

Historical and Future global warming under different RCP emission scenarios

Understanding the relationship between carbon emissions and climate change has become increasingly urgent amidst the universal endorsement of sustainable development and the establishment of net-zero carbon emission target (The Paris Agreement). In this study, model projections based on Coupled Model Intercomparison Project Phase 5 (CMIP5) are used to examine future climate change under different representative concentration pathway (RCP) emission scenarios till 2300. Besides analysis of future global average temperature change under the emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP 8.5, historical data is first collected during the past three decades (1990-2021). The results show that the simulated global warming ranges from 0.9 to 1.3 between 1990 and 2021, consistent with the observations (0.93). Carbon emissions in China arose mostly from manufacturing and construction, electricity and heat and transport. Emissions from electricity, heat and transport increase by a high ratio of 7.7 and 3.5 times due to industry development. Under different RCP scenarios, the global surface temperature anomaly will increase by 0.2-1.0, 1.2-2.0, 3.5-4.3 and 3.0-8.5 , respectively. The surface temperature anomaly values under RCP8.5 are much higher than those under other emission scenarios. Only in the RCP2.6 scenario (sustainability), the surface warming in all simulations stays below a 2 threshold at the end of the 21st century. To attain net zero emissions, it is highly demanded to develop strict emission policies, chart a course toward decarbonization, and institute effective measures aimed at realizing net zero emissions within the short to medium term. Concurrently striving for economic objectives, managing the equilibrium between economic growth and environmental sustainability emerges as a critical imperative.

Risk factors and circulation pattern of respiratory syncytial virus in children under 2years in Maputo, Mozambique.

Evidence on risk factors for respiratory syncytial virus (RSV) in low-resource settings is limited. In Mozambican children <2y of age with severe acute respiratory infection (SARI), we explored risk factors for RSV, described its seasonal variation and assessed associations between RSV and a life-threatening condition. We retrospectively included participants presenting in 2017-2018 in two hospitals in Maputo. RSV was detected and subtyped using real-time quantitative reverse transcription polymerase chain reaction on nasopharyngeal swabs. We used logistic regression and χ2 tests to assess associations and Spearman's correlation coefficient to assess the correlation between weather measurement and RSV positivity. RSV was detected in 23.1% (n=109) of 472 included children and in 50.0% (20/40) of those <3months old. Being <3months (vs >1y) was associated with RSV (adjusted odds ratio 4.3 [95% confidence interval 2.1-8.5]). RSV status was not associated with experiencing a life-threatening condition. RSV A and B co-circulated during the study period, but one type predominated in each year. In 2017, the RSV positivity rate was correlated with monthly average temperature (r=0.793, p=0.002) and precipitation (r=0.596, p=0.041). In Mozambican children with SARI, RSV was prevalent, especially in neonates. However, RSV was not associated with a life-threatening condition.

Impact of Temperature Variations on Rice Production

The mean temperature might rise up to range of 2.0–4.5°C worldwide by the end of this century. Climatic variables affect the growth and development of the crop differently at different growth stages. The rate of development of a crop depends on the climate. Temperature is the primary factor that influences the growth and productivity of crops. Higher or lower temperatures than the optimum lead to improper crop development and affect rice's phenological stages. Extreme temperature may lead to early maturity of the crop and lower temperature lead to prolonged maturity of the crop which in both cases leads to a decrease in yield. A moderate increase in temperature will not have severe implications, but an increase in average temperature by 20 C will likely have strong negative effects on rice crop production. In several studies, it has been reported that high night temperature decreases the yield potential of rice. Whereas, respiratory losses have been shown to increase due to higher day temperature, leaf conductance and net assimilation rates during the day were reported to be higher.

Difference in Cd accumulation among varieties with different growth duration corresponding to typical agro-climate condition in rice ratooning system

IntroductionThe ratoon rice planting area is gradually expanding, but there has been relatively little research on ratoon rice grains contaminated with Cd.MethodsIn this study, five ratoon rice varieties were selected and divided into three groups according to early-maturity (growth duration: 100–110 days), mid-maturity (growth duration: 110–120 days) and late-maturity (growth duration: 120–130 days) varieties. Field experiments were done to study the differences in Cd accumulation among ratoon rice varieties with different growth duration.ResultsThe results showed that the Cd accumulation and concentration of grains spikelet at each growth stage in the main crop were in the order of late-maturity &amp;gt; mid-maturity &amp;gt; early-maturity varieties. However, the trends in Cd concentration and accumulation in grains spikelet during the ratoon crop were the opposite. Analysis found that as the growth duration of the variety extended, the accumulated temperature and daily average temperature in the main crop increased, which significantly increased the translocation factors of Cd from root, stem, and leaf to grains spikelet, and increased the daily average Cd accumulation rate in grains spikelet. The daily average temperature in the ratoon crop increased as the growth duration shortened. The early-maturity variety had higher Cd accumulation in stubble, which promoted the translocation of Cd from the root, stem, and leaf of the plant to the grains spikelet.DiscussionTherefore, appropriately shortening the growth duration of the main crop and extending the growth duration of the ratoon crop are important ways to reduce Cd accumulation in ratoon rice in areas with mild Cd pollution.