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Nitrogen (N) is an essential element for food production. Under the influences of correlated variables of food demand and socio-economic development, a hybrid approach was proposed to identify reactive nitrogen (Nr) loss from livestock-based food and biofuel production systems. The approach included the following components: (1) crop simulation model, DeNitrification-DeComposition, taking into account several field situations and climate change scenarios, and (2) correlation analysis of five types of livestock-based food demand and economic benefits based on copula functions and Markov Chain Monte Carlo simulation. The approach was applied to the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) in China. Production of fodder crops (maize, wheat and soybeans) was examined under two climate change scenarios, Representative Concentration Pathways 4.5 and 8.5. Influence of international trade of soybeans, wheat, and maize on nitrogen fertilization was examined under two additional scenarios. Results showed that compost production from livestock manure and food loss in the production of 1000 kg of livestock-based food would reduce demand for 10.45 kg of urea in crop production, accounting for 9.2%–14.66% of total nitrogen fertilizer demand. Among all livestock-based food, fertilizer demand between 2020 and 2030 is projected to be the highest in fodder crop production to support pork production. Total Nr loss of livestock-based food production in GBA was estimated to be 1.10 to 1.58 Mt under scenario 1, and 1.09 to 1.57 Mt under scenario 2. • Focused on reactive nitrogen loss from livestock and biofuel production system. • A hybrid fodder production and food demand/economic development approach was used. • Used copula–MCMC simulation analysis of joint probabilities of correlated variables. • Reactive nitrogen loss per tonne of pork production would be larger than other livestock-based food in 2020 and 2030. [ABSTRACT FROM AUTHOR]

[Display omitted] • Patch complexity and urban compactness indexes were developed to assess urban form. • The impact of urban form on PM 2.5 was explored in GBA by spatial panel models. • The complexity of urban patches had a negative effect on PM 2.5 concentrations. • The impact of urban compactness on PM 2.5 concentrations was positive. • A more complex and less compact urban form was adoptable in terms of reducing PM 2.5. Given the serious threat of PM 2.5 pollution to the environment and public health in China, reducing PM 2.5 concentrations through urban planning practices has become a common interest of urban planners and policymakers. In this regard, identifying the relationship between urban form and PM 2.5 concentrations has been a matter of much concern. This paper seeks to investigate how urban form influences PM 2.5 concentrations by taking the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as a case study. First, the urban form was assessed by two indicators, i.e., the patch complexity index (PCI) and urban compactness index (UCI), which were developed based on multiple landscape metrics and the principal component analysis. Then, the relationship between PM 2.5 concentrations and the two urban form indicators was revealed by spatial panel models. Our results mainly showed that PCI and UCI were negatively and positively associated with PM 2.5 concentrations, respectively, indicating that less compact urban forms with high patch complexity had advantages in reducing the PM 2.5 concentrations. According to these empirical results, the mixed-use urban development with high green coverage, which is conducive to constructing a more complex and less compact urban form, would be adoptable in terms of mitigating PM 2.5 concentrations in the GBA urban agglomeration. [ABSTRACT FROM AUTHOR]