Impact-oriented water footprint assessment of wheat production in China

Predicting environmental impacts of smallholder wheat production by coupling life cycle assessment and machine learning

Wheat grain production is a vital component of the food supply produced by smallholder farms but faces significant threats from climate change. This study evaluated eight environmental impacts of wheat production using life cycle assessment based on survey data from 274 households, then built random forest models with 21 input features to contrast the environmental responses of different farming practices across three shared socioeconomic pathways (SSPs), spanning from 2024 to 2100. The results indicate significant environmental repercussions. Compared to the baseline period of 2018-2020, a similar upward trend in environmental impacts is observed, showing an average annual growth rate of 5.88 % (ranging from 0.45 to 18.56 %) under the sustainable pathway (SSP119) scenario; 5.90 % (ranging from 1.00 to 18.15 %) for the intermediate development pathway (SSP245); and 6.22 % (ranging from 1.16 to 17.74 %) under the rapid economic development pathway (SSP585). Variation in rainfall is identified as the primary driving factor of the increased environmental impacts, whereas its relationship with rising temperatures is not significant. The results suggest adopting farming practices as a vital strategy for smallholder farms to mitigate climate change impacts. Emphasizing appropriate fertilizer application and straw recycling can significantly reduce the environmental footprint of wheat production. Standardized fertilization could reduce the environmental impact index by 11.10 to 47.83 %, while straw recycling might decrease respiratory inorganics and photochemical oxidant formation potential by over 40 %. Combined, these approaches could lower the impact index by 12.31 to 63.38 %. The findings highlight the importance of adopting enhanced farming practices within smallholder farming systems in the context of climate change. SPOTLIGHTS.

Towards sustainability: An integrated life cycle environmental-economic insight into cow manure management

Waste management signifies an equilibrium between environmental and economic factors. However, a comprehensive understanding of the integrated life cycle environmental-economic performance of waste management activities remains unclear. To facilitate a systematic linkage between the economic and environmental sectors, a regionalized life cycle assessment-based life cycle costing method was developed based on China's actual status quo. The cow manure utilization was set as an entry point to explored long-term environmental-economic performance of milk production under various manure utilization pathways. The results show that trade-offs were observed between internal and external costs as well as various environmental indicators. The choice of waste utilization is the focal point of environmental-economic trade-offs in the cow raising system. The optimal environmental-economic performance was achieved through the manure fertilizer utilization pathway, yielding a remarkable three-fold increase in marginal environmental benefits. Compared with fertilizer utilization, the manure direct returning to field reduced the carbon footprint by 12% while induced an external cost of $14.3. The wastewater treatment pathway is $ 5.5 lower in internal costs but $ 11.7 higher in external costs than those of fertilizer utilization. Overall, utilizing manure has potential to mitigate the upward trend of carbon footprint and external costs. However, achieving the carbon peak remains a significant challenge. A promising solution is the recycling of straw resources within cropping systems, particularly in hotspot regions (e.g., Inner Mongolia, Heilongjiang, Hebei, and Shandong). A comprehensive analysis of the dynamic interplay between cropping systems and cow raising systems is critical steps towards realizing a carbon-neutral future within the dairy production.

Foliar architecture differentially restrains metal sequestration capacity in wheat grains (Triticum aestivum L.) grown in hyper-chloride-contaminated soils

Anthropogenic activities, such as industrial wastewater and use of water softeners, cause hyper-accumulation of Cl- in water sources and soils. Currently, industries have no sustainable method to remove these Cl- ions from wastewater. This study was conducted to evaluate the integrative responses of wheat cultivated in five industrial effluent-affected areas (S2-S6) by investigating soil characters and bioaccumulation of metals in wheat plants and grains. The S4 site (near the second chloride outlet) exhibited a higher concentration of CO2, SO2, NO2, Cl-, Cd, Mn, Ni, Cr, and Zn. Soil from S6 (sewage wastewater downstream getting mixed with chloride-contaminated water) had a minimum level of nutrients (Na, K, and Ca), maximum metals (Cd, Fe, Pb, Mn), and reduction in plant biomass. In site S2 (sewage wastewater upstream of the chloride factory), a higher level of minerals and metals was noted in the roots. Maximum metals in grains occurred in S6 with higher organic osmolytes. The sequestration capacity of metals in leaves was also increased by alterations in anatomical traits. Results indicated that metals and hyper-Cl- concentration employed a negative influence on the plants because of poor soil quality, extremely damaged microstructures leading to reduced yield, poor grain quality, and excessive translocation from roots to wheat grains. These findings revealed that contaminated plants used as either green forage or hay are noxious to animals and if used as grain for feed or humans can lead to serious health hazards.

Comparative analysis of life cycle water accounting of the Lurgi low-pressure methanol production process with biomass or coal as raw materials

Water and energy are both essential for methanol production. This study focuses on the two processes of coal to methanol and biomass to methanol, and analyzes the water footprint of the methanol production process in the life cycle. The results indicate that the water footprint of biomass to methanol is 1707.54 L/MJ, and the dominant factor was the water consumption in the growth stage of biomass, accounting for over 95 % of the total water consumption. The water footprint of the coal to methanol process is 161.40 L/MJ. The main contributor to this process was the methanol stage, which accounted for 99.75 % of the total water footprint. However, the water consumption of the biomass to the methanol stage accounted for only 51.6 % of that of the coal to methanol stage. Based on the power situation of 30 provinces, the indirect water consumption caused by power generation in different regions was calculated, resulting in greater changes in the total water footprint of the biomass to methanol process. Through a sensitivity analysis, the effects of 24 influencing factors and main inputs on the total water consumption were investigated. This study provides the relevant water consumption of the two methanol production processes within the standard range, and the results emphasize the importance of biomass utilization and water conservation.

Inputs for staple crop production in China drive burden shifting of water and carbon footprints transgressing part of provincial planetary boundaries

Crop production is the biggest water user and key contributor to anthropogenic greenhouse gas emissions. Increasing crop yields to ensure adequate food supply under water and land scarcity is excessively dependents on intensive agricultural inputs (such as fertilizers, pesticides, agri-films, or energy), resulting in unintended environmental consequences. Supply chains bringing environmental-intensive inputs from their place of production to the croplands. However, most food-related environmental assessments ignore the environmental burden of agricultural input production, trade, and consumption. Here, we estimate spatially-detailed water (WF) and carbon footprints (CF) of wheat, maize, and rice production in China with extended system boundary from upstream raw material mining to the field. The agricultural inputs account for up to 24% and 89% of a crop's WF and CF, respectively, at the provincial level. The total local generated WF in Chinese northern provinces and CF in Shanxi and Inner Mongolia provinces for producing crops and agricultural inputs transgresses the corresponding downscaled blue water and carbon planetary boundaries. The study broadens the scope of traditional environmental impact assessments in agricultural production and sheds light on the significances to manage the linkages between the crop production and the agricultural inputs' upstream supply chains towards more efficient water use and less greenhouse gas emissions in food system.

Environmental footprints of soybean production in China

As a significant protein source for humans and animals, soybean (Glycine max) has experienced a fast growth with the rapid development of population and economy. Despite broad interest in energy consumption and CO2 emissions generated by soybean production, there are few impact-oriented water footprint assessments of soybean production. This study evaluates the fossil energy, carbon, and water footprints of China's soybean production so that key environmental impacts can be identified. To provide reliable results for decision-making, uncertainty analysis is conducted based on the Monte Carlo model. Results show that the impact on climate change, ecosystem quality, human health, and resources is 3.33 × 103 kg CO2 eq (GSD2 = 1.87), 6.18 × 10-5 Species·yr (GSD2 = 1.81), 3.26 × 10-3 Disability-adjusted Life Years (GSD2 = 1.81), and 81.51 $ (GSD2 = 2.28), respectively. Freshwater ecotoxicity is the dominant contributor (77.69%) to the ecosystem quality category, while climate change (85.22%) is the dominant contributor to the human health category. Key factors analysis results show that diammonium phosphate and diesel, and on-site emissions, are the major contributors to the overall environmental burden of soybean production. Several policy recommendations are proposed, focusing on trade structure optimization, efficient resource use, and technological improvements. Such policy recommendations provide valuable insights to those decision-makers so that they can prepare appropriate mitigation policies.

Exploring the optimal crop planting structure to balance water saving, food security and incomes under the spatiotemporal heterogeneity of the agricultural climate

Crop planting provided foods, generated incomes, and consumed water resources to different extents under different spatiotemporal agroclimatic conditions. For balancing three aspects, targeting the rice, maize, wheat, and sorghum planted in Liaoning during the recent two decades, we established an integrated research framework consisting of water footprint (WF) accounting, clustering analysis, and fuzzy optimization programming to quantify the temporal trends and spatial distribution of water footprints, and optimized the planting structure under the different spatiotemporal agroclimatic conditions. Results showed that the maximum water footprint differences were 4166.73 m³/t and 4790.71 m³/t in spatial distribution and temporal series, respectively. Based on precipitation, we established 12 agroclimatic scenarios according to K-Means clustering. The fuzzy optimization result indicated that the planting area percent ranges of maize, wheat, rice, and sorghum in Liaoning province were 4.96%-98.62%, 0.00%-8.55%, 0.00%-18.18%, and 0.00%-95.04%, respectively under the different spatiotemporal conditions. This study's methods and results help make targeted decisions related to grain planting structure while considering the complex spatial-temporal conditions.

Carbon, energy and water footprints analysis of rapeseed oil production: A case study in China

As the largest consumer of rapeseed oil in the world, China should consider the environmental effect of rapeseed oil production. However, only a few improvement measures have been proposed. To fill this gap, this study analyzed the energy, carbon and water footprints of rapeseed oil production based on the International Organization for Standardization standards using the framework of life cycle assessment. Results show that most of the energy, carbon, and water footprint of rapeseed oil production can be contributed to the direct processes of rapeseed cultivation, and the indirect processes of transport and fertilizer/diesel production. The value of energy and carbon footprints are calculated as 726.07 kg oil eq and 3889.75 kg CO² eq, respectively. For the water footprint, the values of acidification, aquatic eutrophication, carcinogens, freshwater ecotoxicity, water scarcity, and non-carcinogens are 14.24 kg SO₂ eq, 4.53 kg PO₄^-3 eq, 6.72 × 10^-5Case, 5.43 × 10⁴ PAF.m³.d, 437.62 m³ deprived, and 1.88 × 10^-5 case, respectively. Spatial analysis shows that the total environmental impacts of rapeseed production are concentrated in Sichuan, Hunan, Hubei, and Jiangxi Provinces. Correlation analysis reveals the positive correlation of human health and ecosystem quality with fertilizer application and pesticide loss. In general, the environmental effect can be effectively reduced by adjusting the industrial layout to shorten the distance of transport, improve the fine cultivation degree in low-yield areas, and decrease the use of pesticides in the hilly region of southern China.

Potassium phosphate/magnesium oxide modified biochars: Interfacial chemical behaviours and Pb binding performance

Removal of lead (Pb) from aqueous solutions by biochar is a promising method. In this study, wheat straw biochar (WBC) was modified by phosphate/magnesium via pre-treatment of biomass and post-treatment of biochar, noting as WBC_PMA and WBC_PMB, respectively. Based on Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) analyses, phosphate/magnesium chemically bound to the structures of biochar surface, increasing the contents of polar groups (i.e., -COOH and -OH) and phosphorus-containing compounds, mainly Mg₃(PO₄)₂ and Mg₂P₂O₇. Owing to pyrolysis process enhancing loading ability of phosphate/magnesium, WBC_PMA possessed more active functional groups than WBC_PMB. Results showed that maximum sorption capacity of Pb was improved by modifications, following the sequence of WBC_PMA (470.09 mg/g) > WBC_PMB (308.39 mg/g) > WBC (59.93 mg/g). Pseudo-second-order kinetics and thermodynamics study indicated that chemisorption was involved in sorption process. Precipitation, complexation and cation exchange dominated Pb sorption and the corresponding contributions accounted for 17.89-32.73%, 28.84-46.22%, and 21.05-53.27%, respectively. Additionally, desorption characteristics of Pb illustrated that WBC_PMA owned more prominent stabilization ability than that of WBC and WBC_PMB. The findings of this study suggested that pre-modification method increased the contents of active groups in biochar and strengthened the removal efficiency of Pb ultimately. Due to the complexity of the actual Pb-containing wastewater environment, it was necessary to evaluate the effects of various factors on the stabilization performance of the pre-modified biochar in further.

Water footprint coupled economic impact assessment for maize production in China

Nowadays, agricultural production places an enormous burden on freshwater resources, and the environmental external cost caused by the restoration of water quality degradation has attracted great attention. Maize is regarded as one of the world's major food security crops, and China is the second-largest maize producer. Thus, this study conducts an impact-oriented water footprint coupled economic impact assessment to quantify the water-related environmental impacts and economic burden caused by China's maize production from 2008 to 2017. Results show that the overall damage to human health and ecosystem quality of China's maize production in 2017 were 4.32 × 10⁴ DALY and 4.62 × 10³ Species·yr, respectively. The total economic cost was $ 2.15 × 10¹¹, which included an internal cost of $ 5.99 × 10¹⁰ and external cost of $ 1.55 × 10¹¹. Key factor analysis demonstrates that diesel and fertilizer production dominated the reduction in ecological and external cost burdens. Direct water consumption and labor cost played leading roles in human health and internal cost, respectively. The spatiotemporal variation assessment indicates that Inner Mongolia and Heilongjiang were the hotspots for water footprint and economic impact assessment results after considering the yield factor. The national average water footprint and economic impact caused by producing 1 ton of maize showed an upward trend from 2008 to 2015, however, a significant decline transpired later. Overall, improving the resource efficiency (i.e., diesel and freshwater), scientific application of fertilizer and reducing labor input can further lessen the water footprint and economic impact of maize production. Developing the social environment can also generate indirect environmental and economic benefits to China's maize production.

Industrial water pollution and transboundary eco-compensation: analyzing the case of Songhua River Basin, China

As eco-compensation is considered an effective economic instrument for controlling the industrial water pollution in transboundary basin, this study aims to explore a transboundary eco-compensation mechanism for Songhua River Basin that is one of the seven major drainage basins in China. Using a panel dataset of eleven cities in this basin tracked from 1992 to 2016, we empirically examined the environmental Kuznets curve (EKC) hypothesis by analyzing the relationship between economic development and industrial water pollution. Then, we developed two econometric models to quantify the wastewater discharge allowance and eco-compensation of investigated cities, respectively. The results specifically reveal the inverted U-curve effects of GRP (gross regional product) on industrial wastewater discharge, which displays an evidence of EKC in the field of transboundary water pollution in China. Moreover, our results verify the polluter pays principle that polluter should be responsible for its pollution behavior through paying of eco-compensation. Our results further interpret that the emissions trading program can help protect the ecosystem by allowing the wastewater discharge allowance to trading market.

Identification of Major Inefficient Water Consumption Areas Considering Water Consumption, Efficiencies, and Footprints in Australia

Due to population growth, climatic change, and growing water usage, water scarcity is expected to be a more prevalent issue at the global level. The situation in Australia is even more serious because it is the driest continent and is characterized by larger water footprints in the domestic, agriculture and industrial sectors. Because the largest consumption of freshwater resources is in the agricultural sector (59%), this research undertakes a detailed investigation of the water footprints of agricultural practices in Australia. The analysis of the four highest water footprint crops in Australia revealed that the suitability of various crops is connected to the region and the irrigation efficiencies. A desirable crop in one region may be unsuitable in another. The investigation is further extended to analyze the overall virtual water trade of Australia. Australia’s annual virtual water trade balance is adversely biased towards exporting a substantial quantity of water, amounting to 35 km3, per trade data of 2014. It is evident that there is significant potential to reduce water consumption and footprints, and increase the water usage efficiencies, in all sectors. Based on the investigations conducted, it is recommended that the water footprints at each state level be considered at the strategic level. Further detailed analyses are required to reduce the export of a substantial quantity of virtual water considering local demands, export requirements, and production capabilities of regions.

Identifying the Contributions of Multi-Source Data for Winter Wheat Yield Prediction in China

Wheat is a leading cereal grain throughout the world. Timely and reliable wheat yield prediction at a large scale is essential for the agricultural supply chain and global food security, especially in China as an important wheat producing and consuming country. The conventional approach using either climate or satellite data or both to build empirical and crop models has prevailed for decades. However, to what extent climate and satellite data can improve yield prediction is still unknown. In addition, socio-economic (SC) factors may also improve crop yield prediction, but their contributions need in-depth investigation, especially in regions with good irrigation conditions, sufficient fertilization, and pesticide application. Here, we performed the first attempt to predict wheat yield across China from 2001 to 2015 at the county-level by integrating multi-source data, including monthly climate data, satellite data (i.e., Vegetation indices (VIs)), and SC factors. The results show that incorporating all the datasets by using three machine learning methods (Ridge Regression (RR), Random Forest (RF), and Light Gradient Boosting (LightGBM)) can achieve the best performance in yield prediction (R2: 0.68~0.75), with the most individual contributions from climate (~0.53), followed by VIs (~0.45), and SC factors (~0.30). In addition, the combinations of VIs and climate data can capture inter-annual yield variability more effectively than other combinations (e.g., combinations of climate and SC, and combinations of VIs and SC), while combining SC with climate data can better capture spatial yield variability than others. Climate data can provide extra and unique information across the entire growing season, while the peak stage of VIs (Mar.~Apr.) do so. Furthermore, incorporating spatial information and soil proprieties into the benchmark models can improve wheat yield prediction by 0.06 and 0.12, respectively. The optimal wheat prediction can be achieved with approximately a two-month leading time before maturity. Our study develops timely and robust methods for winter wheat yield prediction at a large scale in China, which can be applied to other crops and regions.

An Improved Ecological Footprint Method for Water Resources Utilization Assessment in the Cities

Economic development and increasing population density along the lower reaches of the Yellow river have challenged the river’s ability to meet human and ecological demand. The evaluation of the sustainability of water resources in the lower reaches of the Yellow River is of great significance for the achievement of high-quality development in the region. Based on an improved ecological footprint method considering soil water, the spatial and temporal evolution of the water resources ecological footprint and water resources carrying capacity and evaluates the utilization of water resources in the lower Yellow River are comprehensively evaluated. The results show that agricultural water consumption in the urban agglomerations in the lower reaches of the Yellow River occupies a major position in water consumption, accounting for more than 70%. In 2013–2017, the per capita water resources ecological footprint of the cities along the lower reaches of the Yellow River decreases every year, while the water resources carrying capacity is slightly fluctuating, but remains in a relatively stable state. The deficit situation has eased, falling by 54.52% in the past five years. The water use efficiency of the lower reaches of the Yellow River has increased every year, and the water resources conflict improved significantly, after the implementation of the new environmental policy in 2015. In terms of space, the cities with the smallest per capita ecological deficits include Zibo, Zhengzhou, and Laiwu City, and Dezhou, and Kaifeng and Binzhou City have the largest. Strict water resources management measures and water pollution prevention and control regulations should be formulated to improve the water use efficiency in these areas in order to solve the problem of water shortage.