Biomass energy is a globally recognized renewable energy with zero carbon properties, but its carbon reduction benefits have not been effectively reflected. Based on the whole life cycle evaluation (LCA) method, combined with the economic benefit evaluation method and the environmental impact monetization method, this study built a EGE model for the greenhouse gas emission reduction benefit evaluation (EGE) of straw pyrolysis polygeneration technology. The EGE model took the whole chain of straw collection, off-field storage and transportation, pyrolysis transformation and product utilization as the boundary. The comprehensive economic and environmental benefits of different pyrolysis polygeneration technologies under different production scales was explored. The results showed that the external heating pyrolysis carbon gas co-production technology has the best economic benefits in large-scale application, and at the annual production scale of 0.5×10⁴ ~ 10×10⁴t of straw, each 1t of straw consumption can reduce 1.01−1.07tCO₂eq. Greenhouse gas emission reduction could significantly improve the economic benefits of straw pyrolysis polygeneration technology projects, and each 1t of straw consumption could increase the benefit of 57.5−103.1 yuan, which increased the yield rate of straw pyrolysis polygeneration technology projects by 1.6−14.0PP. It is estimated that the utilization potential of straw in 2030 and 2060 would reach 1.24×10⁸t and 1.67×10⁸t respectively, and the emission reduction income of straw pyrolysis polygeneration technology can reach 1.0×10¹⁰−3.7×10¹⁰ yuan. The results of this study provide technical support for the development of biomass energy industry under the background of realizing the dual-carbon goal.

Ensuring food security and while achieving low-carbon development is a practical issue for the agricultural economy and the priority for carbon neutrality in the planting industry. Based on the time series data of Sichuan planting industry, the change of carbon emission and emission intensity was reviewed, and the input-output super-efficiency model was applied to evaluate the green development efficiency of Sichuan planting industry, and the influencing factors were analyzed by Tobit regression model. The results showed that carbon intensity of Sichuan planting industry decreased from 0.717 t to 0.208 t per 10000 yuan of GDP over the 2010−2022 period, with the continued expansion of the planting area being the core driver of the increase. At the same time, the green development trend of Sichuan planting industry showed the evolution characteristics of "continuous low efficiency− rapid stretching−stable development". In terms of influencing factors, the unique agricultural industrial structure and climate environment, as well as technological investment, have driven the green development of planting industry in Sichuan, while the high proportion of grain and oil crop cultivation was an objective challenge. The fiscal policy had improved the utilization level of planting industry to climate resources, but there was also a significant inhibitory effect. Therefore, while actively adapting to global warming, achieving a long-term balance between food security and green development of the planting industry, and guiding the green development willingness of planting entities with policy orientation, should be a direction that the government should continue to focus on.

The soil moisture product retrieved by single satellite has the disadvantage of discontinuous spatiotemporal coverage. In order to obtain spatiotemporal continuous satellite remote sensing soil moisture data in the Pearl river basin, with the volumetric soil moisture (VSM) product of soil moisture active/passive satellite (SMAP) as a reference, the cumulative distribution function (CDF) method was used to perform the matching bias correction for the VSM products from advanced microwave scanning radiometer 2 (AMSR2), soil moisture and ocean salinity (SMOS) and microwave radiation imager (MWRI), and the optimum interpolation method was used to fuse the data of these four VSM products to generate a spatiotemporal continuous daily fusion VSM product with a resolution of 10km in the Pearl river basin. The station observation data and reanalysis data were adopted to evaluate the fused VSM products. The results indicated that, (1) there were significant differences in the measurement range of soil moisture products retrieved from different satellites. The measurement ranges from high to low were SMOS, AMSR2, SMAP and MWRI, with maximum measurement values of 1.00, 0.99, 0.70 and 0.50m³·m⁻³, respectively. They were not suitable for simultaneous use in soil moisture monitoring. (2) There were deviations between multi-source satellite VSM products. SMOS VSM product had a negative bias compared to SMAP VSM product, with the smallest unbiased root mean square error and the highest correlation coefficient. AMSR2 VSM product had a positive bias compared to SMAP VSM product, and the correlation between these two satellite VSM products was relatively low. MWRI VSM product had a negative bias and the smallest correlation compared to SMAP VSM product. (3) The accuracy and stability of SMAP VSM product were better than those of AMSR2, SMOS and MWRI VSM products. The time series correlation between SMAP VSM product and in-situ data and reanalysis data was obviously better than the latter three satellite VSM products. (4) After CDF matching bias correction, the consistency between AMSR2, SMOS and MWRI VSM products and SMAP VSM product had been enhanced. Multi-source data fusion can correct the error of single satellite product, improve the correlations with in-situ data and reanalysis data, and compensate the spatiotemporal coverage continuity of remote sensing data.

 Climate warming and human activities have a major impact on the spatial and temporal characteristics of surface runoff in the Shiyang river basin, and the adaptive management of water resources in the basin is facing serious challenges. With three independent drainage Dajinghe river system, Liuhe river system and Xidahe river system as the research object, the statistical method analyzed the average flow evolution in 1960−2020, using Mann-Kendall test and Pettitt test to determine the runoff sequence mutation point, set the combination of climate and land use change, and used SWAT model to identify the runoff variation in Shiyang river basin, addressing the unequal allocation of water resources. The results showed that: (1) from 1960 to 2020, the annual average runoff decline rate of Xidahe river, Liuhe river and Dajing river system was 0.01m³·s⁻¹, 0.07m³·s⁻¹, 0.01m³·s⁻¹ respectively. The runoff years for the Liuhe river and Xidahe river were in 1973 and 2002, respectively, while the Dajing river system was in its natural state. (2) The SWAT model had a good adaptability to the Shiyang river basin, and the determination coefficient and the Nash efficiency coefficient were both higher than 0.50. (3) From 1960 to 2020, the contribution of precipitation, average temperature, relative humidity, solar radiation and average wind speed to the annual average runoff were 75%, 53%, 55%, 55%, and 52%, respectively. The contribution of land use change to the annual average runoff was 17%. The coupled contribution of six influence factors to annual average runoff reduction was 67%, indicating that climate change had great influence on runoff in Shiyang river basin. The research results could provide a reference for the adaptive management of watershed water resources.

Exploring the degree of coupling and coordination of agricultural soil and water resources in different regions is of great significance to optimizing the allocation of agricultural soil and water resources and promoting the transformation and development of agricultural production patterns. Based on the data of 117 county-level agricultural land and water resources in Shanxi province, a regional index system was established with reference to previous studies, and methods such as geographic grid, principal component analysis, cluster analysis, and geodetector were used to study the current status of agricultural soil and water resources utilization and dominant factors in Shanxi in-depth. The results showed that Shanxi agricultural soil and water resources could be divided into 4 first-level regions (Region A, Region B, Region C, and Region D) from good to worse, and each first-level region was subdivided into 3 sub-regions, which could be divided into 12 sub-regions in total. The overall difference between the first-level regions was significant: Region A had superior water and heat conditions and better utilization of soil and water resources (arable land index and water resources index of 0.39 and 0.98, respectively, were the best in the four first-level areas), which was mainly distributed in Yuncheng basin in the southwestern part of Shanxi. Region B had good water and heat conditions and higher utilization rate of water resources, but with average utilization of cultivated land, which wa mainly distributed in Fen river basin in the central part of Shanxi, the Yellow river in the western part of Shanxi and Qin river basin in the southeastern part of Shanxi. Region C had better hydrothermal conditions and good utilization of water resources, but relatively poor utilization of arable land, which was mainly located in the Lvliang mountain system and Taihang mountain. Region D had more general hydrothermal conditions and soil and water resource utilization, and was mainly located in northwestern and north of Shanxi. In terms of sub-region division, the three sub-regions in Region A had balanced distribution of soil and water resources, small differences, concentrated distribution, and balanced region share. Region B was dominated by the sub-region with adequate agricultural water utilization, and its distribution was more concentrated. Region C was dominated by the sub-region of insufficient agricultural water utilization and its contiguous distribution, and the other two sub-regions were small in region and dispersed. Region D was dominated by the sub-region of upgraded agricultural water irrigation, but its distribution was more scattered. Changes in the soil and water resources system in Shanxi were mainly driven by natural factors, and the influences were, in descending order, the water resources index (0.4961), the proportion of water used in agriculture (0.4815), the annual average temperature (0.4480), the irrigation rate of cultivated land (0.4387), and the effective cumulative temperature ≥10℃ (0.4190), among which the interactions of the average annual temperature and the irrigation rate of arable land were the most significant. The results of this study can provide a reference for optimizing the agricultural planting structure in Shanxi.

Typical temperature characteristic of cold air pool (CAP) in the main producing areas of Xihu Longjing plantation was analyzed using data from 29 automatic meteorological stations and radar sounding inversion data during spring tea budding period in 2021. A method was explored to automatically identify areas prone CAP under complex terrain. The results showed that the occurrence frequency of CAP day was 45% in typical prone CAP areas of Xihu Longjing plantation from February 20 to March 31, 2021. The occurrence frequency and intensity of CAP were related to weather types. CAP was more likely to occur on sunny and cloudy weather conditions, less on overcast weather conditions, and strong CAP days predominantly appearing under clear sky conditions. CAP increased the frequency and intensity of inversions, with an increase of 23% in inversion frequency, and an increase of 1.26℃ per 100m in average maximum inversion intensity compared to flat areas. A typical daily variation of CAP included three stages: formation and strengthening, maintenance, and weakening and dissipation, with the maximum hourly temperature increase at the valley during the weakening and dissipation stage reaching 11.3℃·h⁻¹, which was 4.1℃·h⁻¹ higher than the maximum hourly temperature decrease during the formation and strengthening stage (7.2℃·h⁻¹). To identify the CAP prone areas, three terrain factors in DEM data including slope, percentile of height relative to surroundings, and terrain curvature were constructed as discriminant indicators showing good identification effectiveness. Coincidence rates of stations located in CAP prone and non prone areas were 80% and 78% respectively. About 26% of the tea plantation in study area was located in CAP prone areas, making them more susceptible to spring tea frost damage during the budding period due to extreme low temperatures and rapid warming processes.

Agricultural film residues which limit crop growth and cause soil pollution become increasingly serious. Exploring the effects of agricultural film residues with different amounts on the growth of maize and soil environment can provide theoretical support for the scientific and rational use of agricultural film. In this study, the distribution of residual film in maize farmland with film mulching in Hetao irrigation region of Inner Mongolia was taken as the research object, and 6 residual film gradients were set, including 0 (CK), 75kg·ha⁻¹, 150kg·ha⁻¹, 300kg·ha⁻¹, 450kg·ha⁻¹ and 600kg·ha⁻¹, and the effects of different amounts of the agricultural film residues on maize yield and its components, root weight and taproot number, soil moisture content and bulk density were analyzed. The results showed that: (1) there was a negative correlation between the amount of film residues and the yield of maize, and there was a significant difference in the yield when the amount of film residues exceeded 300kg·ha⁻¹ (P<0.05). With the increase of film residues, the bald tip of maize increased, and the 100-grain weight decreased significantly (P<0.05). (2) The increase of the film residues reduced the root quality and taproot numbers of maize, which were not conductive to the growth and development of the root system, and the ability of the root system to absorb water and nutrients from the soil decreased. (3) The film residues hindered the transport of soil water, soil water seeped slowly when the amount of film residues reached 300−450kg·ha⁻¹, and the film residues over 600kg·ha⁻¹ hindered the migration of soil capillary water and the infiltration of precipitation. Therefore, the use of scientific and reasonable ways to control soil residual film pollution control and recycle plastic film to reduce plastic film residues in the soil is helpful to promote the improvement of maize yield and soil quality, and realize the green and sustainable development of agriculture.

The soil temperature in the eastern foothills of the Helan mountain, where wine grapes are buried in layers of soil during winter and spring, is important for grape growth and annual yields. Therefore, the variation law of soil temperature in buried soil layers for different soil types has been analyzed to provide a reference for scientific management of planting sites. In the winter to spring of 2021/2022 and 2022/2023, four buried soil layers with different soil types were selected at the eastern foot of Helan mountain, site 1(F1): heavy stone and sandy soil; Site 2(F2): 40% stony soil and 60% sandy soil; Site 3(F3): light lime soil; Site 4(F4): fine sandy soil, and the soil temperature at 10cm (T1), 20cm (T2), 30cm (T3) and 40cm (T4) from the surface soil was monitored in real time, to analyze the characteristics of soil temperature changes of buried soil layer in winter (December to February of the next year) and spring (March to the excavation). The results showed that: (1) in winter, the daily mean soil temperature and the daily minimum soil temperature fluctuated in line with the trend of the air temperature, and the fluctuations decreased as the soil depth increases. The maximum difference in average temperature and average minimum temperature of buried soil layers at the same depth at test site 1 to 3 were 1.2℃ and 2.2℃, respectively. The temperature of the buried soil layer in F4 was lower than that at the other test sites. With the increase of buried soil depth, the average soil temperature and the minimum soil temperature increased by 0.2−1.3℃ and 0.9−2.2℃ per 10cm. (2) The starting date of the lowest 5 days of buried soil temperature for each test appeared within 1d after the cooling process. The occurrence time of the daily minimum soil temperature in the buried soil layer was gradually delayed as the depth of buried layer increased, and the duration of the low temperature was extended. (3) In spring, the average daily soil temperature decreased gradually with increasing depth, and decreased by 0.1−1.2℃ every 10cm. The accumulated temperature of ≥10℃ increased with time in a single linear relationship, the accumulated temperature of T1 and T2, T3 and T4 had little difference, with a daily growth rate of 13.1−14.4℃ and 12.2−13.7℃, the average accumulated temperature difference of T1/T2 and T3/T4 was 25.4−33.8℃·d. Based on the soil temperature index of Cabernet Sauvignon germination, the ≥10℃ accumulated temperature of germination start date from T2 to T4 was 277.9−307.6℃·d. (4) The relationship equation between ≥10℃ active accumulated soil temperature and ≥10℃ air accumulated temperature was established for buried soil T1/T2 and T3/T4 in test site F1−F3. It can be seen that the equations show the change trend of one variable equation, and the fitting effect was good, the efficiency coefficients of models were above 0.95, and the average absolute error was below 22.4℃·d. In conclusion, the risk of overwintering freeze damage to grape branches is small in different types of soil layers buried during winter, and the temperature of the buried layer increases with depth, with a gradual decrease in fluctuation. The temperature of fine sandy soil is slightly lower than that of other soil types. The ≥10℃ active accumulated temperature index of grape soil germination starting date and the linear relationship model between air accumulated temperature and buried soil accumulated temperature in spring can provide reference for spring excavation.

This paper utilized methods such as the MaxEnt model and ArcGIS, selected 47 actual planting points of Brassica juncea var. tumida and 20 environmental impact factors, and combined with the data of three future climate scenarios introduced by CMIP6 to predict the suitable climate areas of Brassica juncea var. tumida in Chongqing in the 2050s (2041−2060) and 2070s (2061−2080), providing a scientific reference for the planning and layout of Brassica juncea var. tumida planting in Chongqing. The results showed that the MaxEnt model provided excellent predictions. The cumulative contribution of dominant factors reached as high as 88.3%, including precipitation of the wettest month, annual precipitation, altitude, mean temperature of the coldest season, annual mean temperature and temperature annual range. The threshold of those factors was 178−185mm, 1170−1225mm, 100−380m, 7.8−9.0℃, 17.5−18.6℃ and 27.6−28.6℃, respectively. Under current conditions, Brassica juncea var. tumida had 11.6% of the suitable areas, including 1422 km² of the highly suitable area  and 1.7% were in Fuling, Fengdu, and Zhongxian. Under the SSP1−2.6, SSP2−4.5 and SSP5−8.5 climate scenarios, in the 2050s the suitable areas amounted to 11.0%, 11.4% and 11.2%, respectively, and in the 2070s the suitable areas amounted to 10.8%, 10.6% and 9.6%. Future climate change will have adversely affect the planting and development of Brassica juncea var. tumida. To reduce these adverse effects, suitable planting areas should be selected.

To study the impact of different varieties and planting densities on the transpiration rate of cotton in Xinjiang, a field experiment was conducted in 2022 in Wulanwusu, Xinjiang. Three cotton varieties (' Zhongmian 979'  ' Zhongmian 703'  and 'Guoxin cotton' ) and two planting densities (D1:22 plants·m⁻²; D2:11 plants·m⁻²) were establish for treatment. The transpiration rate was measured using a heat ratio stem flow meter, and the differences in daily average transpiration, daily transpiration change, and cumulative transpiration of cotton under different weather conditions (sunny, rainy) and time scales were compared to clarify the water consumption rules of cotton under different varieties and densities in northern Xinjiang. The results showed that: (1) planting density had a significant impact on the cumulative and daily transpiration rates of cotton population. The cumulative and daily transpiration rates of cotton increased significantly under D1 planting density. Under D1 planting density treatment, the cumulative and daily transpiration rates of three varieties were significantly higher than those under D2 planting density treatment (an average increase of 51.2%). (2) Cotton varieties had a significant impact on individual and group transpiration, with ' Zhongmian 703'  higher stem flow rate, daily transpiration rate, and cumulative transpiration than other varieties. (3) The transpiration of a single cotton plant showed a "几" shaped variation pattern on a daily scale. During the day (9：00−21：00), the transpiration was relatively stable, but there was still a slight stem flow at night due to root pressure. (4) The transpiration rate and amount of cotton decreased month by month from July to September. The daily transpiration curve of cotton in September gradually transitioned to a unimodal pattern, and the daytime transpiration starts later (10：00) and ends earlier (20：00). (5) Accumulated transpiration had a positive correlation with both seed cotton yield and average leaf area, but it was not significant.

 Watermelon Jing xin No.4 and pumpkin Jingxinzhen No.4 were used as test materials, and LED pure white light was taken as control (CK). Five treatments were set, namely, red-blue light alternating at 1 hour interval (R/B1), red-blue mixed light (RB), red-blue light alternating at 6 hours interval (R/B6), pure blue light (B) and pure red light (R). Besides, experiments were carried out in a fully artificial light plant to delve into the optimal light formula for the growth and development of watermelon and Pumpkin seedlings. The results showed as follows: (1) the absolute growth rate of plant height, stem diameter and leaf area of watermelon seedlings under R/B6 treatment were increased by 77.2%, 110.7% and 68.5% compared with the control, respectively; the number of leaves of watermelon seedlings under R/B1 treatment was significantly increased by 78.6% compared with the control at 40d (P<0.05). Under R/B1 treatment, the absolute growth rate of pumpkin seedling height and the number of leaves at 40d after planting were significantly increased by 211% and 18% (P<0.05), respectively, and the absolute growth rate of stem diameter was increased by 85%. (2) The crude polysaccharide content of watermelon and pumpkin seedlings under R treatment was increased by 25.5% and 13.4% compared with the control (P<0.05), and the crude protein content of watermelon seedlings under B treatment was increased by 9.4% compared with the control, and the chlorophyll content of watermelon and pumpkin seedlings under RB treatment was higher than that under the control 10 to 40 days after planting. Watermelon and pumpkin seedlings treated with RB showed a 1.8% and 0.3% increase in chlorophyll content, respectively, on the 40th day after planting, compared to control plants. (3) At 40th day after implantation, PI_abs of watermelon seedlings under B and R/B6 treatments were 2.8 times and 1.1 times higher than that of control, respectively. Pumpkin seedlings treated with R/B1 and R/B6 had 110% times and 34% higher PI_abs, respectively, than control seedlings. In summary, alternating irradiation of watermelon and pumpkin seedlings with red and blue light effectively improved the growth and development of watermelon and pumpkin seedlings and enhanced the chlorophyll fluorescence performance, while blue light can increased the crude protein content and red light can increase the crude polysaccharide content. Thus, when watermelon and pumpkin seedlings are cultured in a uniform manner, alternating red and blue light can maximize the seedling quality and provide high-quality seedlings for factory production.

 Whether irrigation water with low temperature could affect the temperatures of rice plants (including flag leaves, panicles and stems) under high air temperature remains unknown now. A field experiment was conducted with a split-plot design under field conditions. The experiment included four treatments, i.e. high air temperature with irrigation water of low temperature, high air temperature with irrigation water of normal temperature, natural air temperature with irrigation water of low temperature and natural air temperature with irrigation water of normal temperature, during which irrigation water temperature treatments were regarded as main plots (initial water temperature 20.0℃ for cold water irrigation treatment and initial water temperature 27.7℃ for irrigation with normal temperature) and air temperature treatments were seemed as subplots (the average air temperature 38.0℃ for high air temperature treatment and the average air temperature 32.0℃ for natural air temperature treatment). The change characteristics of rice plant temperatures and the effect of irrigation with cold water and normal temperature water on the temperatures of rice flag leaves, panicles and internodes were explored in this paper. The experimental results indicated that, under high air temperature, the temperatures of rice flag leaves, panicles and the internodes were markedly enhanced by 5.9℃, 5.7℃ and 0.9℃, respectively, as compared with those for natural air temperature. Under high air temperature, the water temperature for irrigation with cold water treatment increased faster and changed larger than that for irrigation with normal temperature water, with the former increasing by 6.0℃ from 10：00 to 15：00 while the latter increasing only by 2.3℃ from 10：00 to 15：00. The phenomenon suggested that the cold water could absorb more energy from surrounding environment than normal temperature water under high air temperature. Therefore, under high air temperature, the irrigation with cold water treatment pronouncedly decreased the temperatures of flag leaves, panicles and the internodes by 1.5℃, 1.3℃ and 1.6℃, respectively, furthermore, increased the temperature differences between air and flag leaves, between air and panicles and between air and internodes, as compared to those for irrigation with normal temperature water treatment. Irrigation with cold water could significantly reduce organs temperatures within rice plants under high air temperature, which played a key role in alleviating heat-stress. Correspondingly, it should be considered as a method to mitigate high air temperature damage in rice production.