Field experiments were carried out in Huantai County from 2006 to 2008 to evaluate the effects of different nitrogen (N) fertilization and irrigation management practices on water leakage and nitrate leaching in the dominant wheat–maize rotation system in the North China Plain (NCP). Two N fertilization (NF₁, the traditional one; NF₂, fertilization based on soil testing) and two irrigation (IR₁, the traditional one; IR₂, irrigation based on real-time soil water content monitoring) management practices were designed in the experiments. Water and nitrate amounts leaving the soil layer at a depth of 2.0 m below the soil surface were calculated and compared. Results showed that the IR₂ effectively reduced water leakage and nitrate leaching amounts in the two-year period, especially in the winter wheat season. Less than 10 percent irrigation water could be saved in a dry winter wheat season, but about 60 percent could be saved in a wet winter wheat season. Besides, 58.8 percent nitrate under single NF₂IR₁ and 85.2 percent under NF₂IR₂ could be prevented from leaching. The IR₂ should be considered as the best management practice to save groundwater resources and prevent nitrate from leaching. The amounts of N input play a great role in affecting nitrate concentrations in the soil solutions in the winter wheat–summer maize rotation system. The NF₂ significantly reduced N inputs and should be encouraged in ordinary agricultural production. Thus, nitrate leaching and groundwater contamination could be alleviated, but timely N supplement might be needed under high precipitation condition.

Livestock farming sector is an important anthropogenic emission source of ammonia (NH3) and greenhouse gases including nitrous oxide (N2O) and methane (CH4). The NH3, not N2O and CH4, is known as an important gaseous precursor to cause atmospheric particulate matter (PM) pollution. However, the relationship between livestock-derived NH3 and atmospheric PM pollution has not been sufficiently investigated, especially in the developed regions with serious air pollution. Here, we studied the spatio-temporal emissions of NH3, N2O and CH4 from livestock farming as well as the relationship between livestock NH3 emission and atmospheric PM pollution in the Beijing-Tianjin-Hebei Region, one of the most developed and air polluted area in China. Over the past 40 years, livestock-derived emissions of NH3, N2O and CH4 had experienced four temporal stages (1978-1990: low level; 1991-1995: rapid growth; 1996-2005: reached hot moments; 2006-2018: stable at a high level). Livestock-derived emissions of NH3, N2O and CH4 were 813, 19 and 499 Gg in 2017, respectively. The southeastern plain was the hotspot, and the pig and cattle were the main sources (78-99%) of NH3, N2O and CH4 in livestock farming. The livestock-derived NH3 emission explained approximately a quarter of the variations of atmospheric PM2.5 (size ≤2.5 μm) (24%) and PM10 (size ≤10 μm) (22%) pollution. Based on the knowledge of atmospheric chemical processes, we concluded that the livestock-derived NH3 emission significantly affected atmospheric PM2.5 and PM10 pollution in the Beijing-Tianjin-Hebei Region. Consequently, the livestock farming, especially pig and cattle breeding, should be paid more attention in the context of atmospheric particulate matter pollution and regional greenhouse gases management.

Livestock and poultry farming sectors are among the largest anthropogenic methane (CH₄) emission sources, mainly from enteric fermentation and manure management. Previous inventories of CH₄ emission were generally based on constant emission factor (EF) per head, which had some weaknesses mainly due to the succession of breeding and feeding systems over decades. Here, more reliable long-term changes of CH₄ emissions from livestock and poultry farming in Beijing are estimated using the dynamic EFs based on the Intergovernmental Panel on Climate Change (IPCC) Tier 2 method, and high-resolution spatial patterns of CH₄ emissions are also estimated with intensive field survey. The results showed that the estimated CH₄ emissions derived by dynamic EFs were approximately 13–19% lower than those based on the constant EF before 2010. After 2011, however, the dynamic EFs-derived CH₄ emissions were a little higher (3%) than the constant EF method. Temporal CH₄ emissions in Beijing had experienced four developing stages (1978–1988: stable; 1989–1998: slow growth; 1999–2004: rapid growth and reached hot moments; 2005–2014: decline) during 1978–2014. Over the first two decades, the contributions of pigs (45%) and cattle (46%) to annual CH₄ emission were similar; subsequently, the cattle emitted more CH₄ compared to the pigs. At a spatial scale, Shunyi, Daxing, and Tongzhou districts with more cattle and pigs are the hotspots of CH₄ emission. In conclusion, the dynamic EFs method obviously improved the spatio-temporal estimates of CH₄ emissions compared to the constant EF approach, and the improvements depended on the period and aquaculture structure. Therefore, the dynamic EFs method should be recommended for estimating CH₄ emissions from livestock and poultry farming in the future.