• Energy Research

China’s industry accounts for 46.8% of the national Gross Domestic Product (GDP) and plays an important strategic role in its economic growth. On the other hand, industrial wastewater is also the major source of water pollution. In order to examine the relationship between the underlying driving forces and various environmental indicators, values of two critical industrial wastewater pollutant discharge parameters (Chemical Oxygen Demand (COD) and ammonia nitrogen (NH4-N)), between 2001 and 2009, were decomposed into three factors: i.e., production effects (caused by change in the scale of economic activity), structure effects (caused by change in economic structure) and intensity effects (caused by change in technological level of each sector), using additive version of the Logarithmic Mean Divisia Index (LMDI I) decomposition method. Results showed that: (1) the average annual effect of COD discharges in China was −2.99%, whereas the production effect, the structure effect, and the intensity effect were 14.64%, −1.39%, and −16.24%, respectively. Similarly, the average effect of NH4-N discharges was −4.03%, while the production effect, the structure effect, and the intensity effect were 16.18%, −2.88%, and −17.33%, respectively; (2) the production effect was the major factor responsible for the increase in COD and NH4-N discharges, accounting for 45% and 44% of the total contribution, respectively; (3) the intensity effect, which accounted for 50% and 48% of the total contribution, respectively, exerted a dominant decremental effect on COD and NH4-N discharges; intensity effect was further decomposed into cleaner production effect and pollution abatement effect with the cleaner production effect accounting for 60% and 55% of the reduction of COD and NH4-N, respectively; (4) the major contributors to incremental COD and NH4-N discharges were divided among industrial sub-sectors and the top contributors were identified. Potential restructuring and regulation measures were proposed for pollutant reduction.

Pour mieux comprendre l'application mondiale des modèles de prédiction de l'érosion des sols, nous avons examiné de manière approfondie la littérature de recherche pertinente évaluée par des pairs sur la modélisation de l'érosion des sols publiée entre 1994 et 2017. Nous avons cherché à identifier (i) les processus et les modèles les plus fréquemment abordés dans la littérature, (ii) les régions dans lesquelles les modèles sont principalement appliqués, (iii) les régions qui restent non traitées et pourquoi, et (iv) la fréquence des études menées pour valider/évaluer les résultats des modèles par rapport aux données mesurées. Pour mener à bien cette tâche, nous avons combiné les connaissances collectives de 67 scientifiques spécialistes de l'érosion des sols de 25 pays. La base de données résultante, intitulée « Global Applications of Soil Erosion Modelling Tracker (GASEMT) », comprend 3030 enregistrements de modélisation individuels provenant de 126 pays, englobant tous les continents (à l'exception de l'Antarctique). Sur les 8471 articles identifiés comme potentiellement pertinents, nous avons examiné 1697 articles appropriés et systématiquement évalué et transféré 42 attributs pertinents dans la base de données. Cette base de données GASEMT fournit des informations complètes sur l'état de l'art des modèles d'érosion des sols et des applications de modèles dans le monde entier. Cette base de données vise à soutenir la prochaine évaluation mondiale de l'érosion des sols par les Nations Unies basée sur les pays, en plus d'aider à éclairer les priorités de recherche sur l'érosion des sols en construisant une base pour de futures analyses ciblées et approfondies. GASEMT est une base de données open-source à la disposition de l'ensemble de la communauté des utilisateurs pour développer la recherche, corriger les erreurs et faire des extensions futures. Para comprender mejor la aplicación global de los modelos de predicción de la erosión del suelo, revisamos exhaustivamente la literatura de investigación relevante revisada por pares sobre modelos de erosión del suelo publicada entre 1994 y 2017. Nuestro objetivo fue identificar (i) los procesos y modelos abordados con mayor frecuencia en la literatura, (ii) las regiones dentro de las cuales se aplican principalmente los modelos, (iii) las regiones que permanecen sin abordar y por qué, y (iv) con qué frecuencia se realizan estudios para validar/evaluar los resultados del modelo en relación con los datos medidos. Para realizar esta tarea, combinamos el conocimiento colectivo de 67 científicos de erosión de suelos de 25 países. La base de datos resultante, denominada 'Global Applications of Soil Erosion Modelling Tracker (GASEMT)', incluye 3030 registros de modelado individuales de 126 países, que abarcan todos los continentes (excepto la Antártida). De los 8471 artículos identificados como potencialmente relevantes, revisamos 1697 artículos apropiados y evaluamos y transferimos sistemáticamente 42 atributos relevantes a la base de datos. Esta base de datos GASEMT proporciona información integral sobre el estado del arte de los modelos de erosión del suelo y las aplicaciones de modelos en todo el mundo. Esta base de datos tiene la intención de apoyar la próxima evaluación mundial de la erosión del suelo de las Naciones Unidas basada en los países, además de ayudar a informar las prioridades de investigación de la erosión del suelo mediante la creación de una base para futuros análisis específicos y en profundidad. GASEMT es una base de datos de código abierto disponible para toda la comunidad de usuarios para desarrollar investigaciones, rectificar errores y realizar futuras expansiones. To gain a better understanding of the global application of soil erosion prediction models, we comprehensively reviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and 2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the regions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv) how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To perform this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. The resulting database, named 'Global Applications of Soil Erosion Modelling Tracker (GASEMT)', includes 3030 individual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471 articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluated and transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insights into the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to support the upcoming country-based United Nations global soil-erosion assessment in addition to helping to inform soil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is an open-source database available to the entire user-community to develop research, rectify errors, and make future expansions. للحصول على فهم أفضل للتطبيق العالمي لنماذج التنبؤ بتآكل التربة، قمنا بمراجعة شاملة للأدبيات البحثية ذات الصلة التي استعرضها الأقران حول نمذجة تآكل التربة المنشورة بين عامي 1994 و 2017. كنا نهدف إلى تحديد (1) العمليات والنماذج التي يتم تناولها بشكل متكرر في الأدبيات، (2) المناطق التي يتم فيها تطبيق النماذج في المقام الأول، (3) المناطق التي لا تزال دون معالجة ولماذا، و (4) عدد المرات التي يتم فيها إجراء دراسات للتحقق من صحة/تقييم نتائج النموذج بالنسبة للبيانات المقاسة. لأداء هذه المهمة، جمعنا المعرفة الجماعية لـ 67 عالمًا في مجال تآكل التربة من 25 دولة. تتضمن قاعدة البيانات الناتجة، المسماة "التطبيقات العالمية لتتبع نمذجة تآكل التربة (GASEMT )"، 3030 سجل نمذجة فردي من 126 دولة، تشمل جميع القارات (باستثناء القارة القطبية الجنوبية). من بين 8471 مقالة تم تحديدها على أنها ذات صلة محتملة، قمنا بمراجعة 1697 مقالة مناسبة وقمنا بتقييم ونقل 42 سمة ذات صلة بشكل منهجي إلى قاعدة البيانات. توفر قاعدة بيانات GASEMT هذه رؤى شاملة حول أحدث نماذج تآكل التربة وتطبيقات النماذج في جميع أنحاء العالم. تهدف قاعدة البيانات هذه إلى دعم التقييم العالمي المقبل لتآكل التربة الذي تجريه الأمم المتحدة على المستوى القطري بالإضافة إلى المساعدة في توجيه أولويات أبحاث تآكل التربة من خلال بناء أساس للتحليلات المتعمقة المستهدفة في المستقبل. GASEMT هي قاعدة بيانات مفتوحة المصدر متاحة لمجتمع المستخدمين بأكمله لتطوير البحث وتصحيح الأخطاء وإجراء التوسعات المستقبلية.

Numerous index decomposition analysis approaches have been reported in the past 30 years. However, the selection of different methods appears to be arbitrary, and little consensus has been reached on which is the superior method. Between 2001 and 2009, 10 different methods have been used to identify the factors (i.e. production effect, structural effect and intensity effect) influencing on China’s industrial wastewater pollutant (Chemical Oxygen Demand, COD) discharges. From the aspect of theoretical foundation, adaptability, ease of use, and ease of result interpretation, these methods are compared. Results show that: (1) LMDI 1 is a superior approach because of zero residual error in decomposition, no zero values problem in data set, simplicity in formula, and wide range in usage situations. (2) the average effect changes of industrial wastewater changes of COD discharges in China is 14.89 ×104 t with production effect, structural effect, and intensity effect were 72.97×104 t, -6.93×104 t and -80.94×104 t, respectively. (3) production effect was the major factor responsible for the rise of COD discharges, accounting for 45% of the total contribution. (4) structural effect contributed to the decrease of COD discharges with a small effect of 4% in total contribution. (5) intensity effect had an dominant decremental effect in COD discharges.

China’s industry accounts for 46.8% of the national gross domestic product (GDP) and plays an important strategic role to its economic growth, but it is also the main water pollution sources. In order to identify the relationship between the underlying driving forces and various environmental indicators, two critical industrial wastewater pollutant discharges over 2001-2009, including Chemical Oxygen Demand (COD) and ammonia nitrogen (NH4-N), were decomposed into three factors, i.e., production effect (caused by change in the scale of economic activity), structural effect (caused by change in economic structure) and intensity effect (caused by change in technological level of the sector), using a logarithmic mean Divisia index I (LMDI I) decomposition method. Results showed that: (1) the average annual effect changes of industrial wastewater changes of COD discharges in China is -2.99% with the production effect, structural effect, and intensity effect as 14.64%, -1.39%, and -16.24%, respectively. Similarly, the average effect changes of industrial wastewater changes of NH4-N discharges is -4.03% with production effect, structural effect, and intensity effect as 16.18%, -2.88%, and -17.33%, respectively. (2) production effect was the major factor responsible for the rise of COD and NH4-N discharges, accounting for 45% and 44% of the total contribution. (3) structural effect contributed to the decrease of COD and NH4-N discharges with a small effect of 4% and 8% in total contribution. (4) intensity effect had an dominant decremental effect in COD and NH4-N discharges, accounting for 50% and 48% of the total contribution; intensity effect could be further decomposed in cleaner production effect and pollution abatement effect, and cleaner production effect of COD and NH4-N accounts for 60% and 55% in pollution reduction. (5) the main contributors to incremental COD and NH4-N discharges among industrial sub-sectors were manufacture of paper and paper products, processing of food from agricultural products, manufacture of textile and so on. These sectors should be the top priorities for policy makers to reduce pollutants discharges, and the potential measures are industrial restructuring and related regulation.

Synergistically maintain or enhance the numerous beneficial contributions of nature to the quality of human life is an important but challenging question for achieving Sustainable Development Goals. However, the spatiotemporal distributions of global nature's contributions to people (NCPs) and their interactions remain unclear. We built a rapid assessment indicator framework and produced the first spatially explicit assessment of all 18 NCPs at a global scale. The 18 global NCPs in 1992 and 2018 were globally assessed in 15,204 subbasins based on two spatial indicator dimensions, including nature's potential contribution and the actual contribution to people. The results show that most of the high NCP values are highly localized. From 1992 to 2018, 6 regulating NCPs, 3 material NCPs, and 2 nonmaterial NCPs declined; 29 regulating-material NCP combinations (54 in total) dominated 76% of the terrestrial area, and the area with few NCPs accounted for 22%; and synergistic relationships were more common than tradeoff relationships, while the relationships among regulating and material NCPs generally traded-off with each other. Transitional climate areas contained few NCPs and have strong tradeoff relationships. However, the high synergistic relationship among NCPs in low latitudes could be threatened by future climate change. These findings provide a general spatiotemporal understanding of global NCP distributions and can be used to interpret the biogeographic information in a functional way to support regional coordination and achieve landscape multifunctionality for the enhancement of human well-being.