Rapidly changing high-latitude seasonality: Implications for the 21st century carbon cycle in Alaska

Seasonal variations in high-latitude terrestrial carbon (C) fluxes are predominantly driven by air temperature and radiation. At present, high-latitude net C uptake is largest during the summer. Recent observations and modeling studies have demonstrated that ongoing and projected climate change will increase plant productivity, microbial respiration, and growing season lengths at high-latitudes, but impacts on high-latitude C cycle seasonality (and potential feedbacks to the climate system) remain uncertain. Here we use ecosys, a well-tested and process-rich mechanistic ecosystem model that we evaluate further in this study, to explore how climate warming under an RCP8.5 scenario will shift C cycle seasonality in Alaska throughout the 21st century. The model successfully reproduced recently reported large high-latitude C losses during the fall and winter and yet still predicts a high-latitude C sink, pointing to a resolution of the current conflict between process-model and observation-based estimates of high-latitude C balance. We find that warming will result in surprisingly large changes in net ecosystem exchange (NEE; defined as negative for uptake) seasonality, with spring net C uptake overtaking summer net C uptake by year 2100. This shift is driven by a factor of 3 relaxation of spring temperature limitation to plant productivity that results in earlier C uptake and a corresponding increase in magnitude of spring NEE from -19 to -144 gC m-2 season-1 by the end of the century. Although a similar relaxation of temperature limitation will occur in the fall, radiation limitation during those months will limit increases in C fixation. Additionally, warmer soil temperatures and increased carbon inputs from plants lead to combined fall and winter C losses (163 gC m-2) that are larger than summer net uptake (123 gC m-2 season-1) by year 2100. However, this increase in microbial activity leads to more rapid N cycling and increased plant N uptake during the fall and winter months that supports large increases in spring NPP. Due to the large increases in spring net C uptake, the high-latitude atmospheric C sink is projected to sustain throughout this century. Our analysis disentangles the effects of key environmental drivers of high-latitude seasonal C balances as climate changes over the 21st century.

Waste Heat Recovery by Air-to-Water Heat Pump from Exhausted Ventilating Air for Heating of Multi-Family Residential Buildings

The paper presents an analysis of the application of an air-to-water electric compressor heat pump (AWHP) for the recovery of waste heat from the exhaust air in a typical multifamily residential building and the use of this heat for space heating, as well as the impact of this solution on the building energy performance (the PPR index). Simulations were performed in TRNSYS for five locations in Poland (Koszalin, Wrocław, Lublin, Białystok, Suwałki), for various heating system parameters (80/60 °C, 75/65 °C, 70/50 °C, 55/45 °C, 35/28 °C), for various temperature limitations of heat pump operation. It was shown that the analyzed system has great potential from an energy and environmental point of view. It can provide significant benefits in terms of the energy performance of the building, depending on the system parameters. The results show that the most energy-efficient system is the one with the lowest heating system temperatures. Moreover, implementing a temperature limitation on the heat pump operation improves its efficiency, but the higher the design parameters of the heating installation and the lower the limitation, the lower the heat pump contribution, and the higher the SCOP and the PPR. The energy effect is also influenced by location, but its scale depends on the parameters of the heating system and the temperature limitation of the heat pump’s operation. It is more significant for lower heating system parameters. This system enables the possibility of further reducing the demand for nonrenewable primary energy by powering the heat pump with photovoltaic cells.

Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model-data fusion framework

The flow of carbon through terrestrial ecosystems and the response to climate is a critical but highly uncertain process in the global carbon cycle. However, with a rapidly expanding array of in situ and satellite data, there is an opportunity to improve our mechanistic understanding of the carbon (C) cycle’s response to land use and climate change. Uncertainty in temperature limitation on productivity pose a significant challenge to predicting the response of ecosystem carbon fluxes to a changing climate. Here we diagnose and quantitatively resolve environmental limitations on growing season onset of gross primary production (GPP) using nearly two decades of meteorological and C flux data (2000–2018) at a subalpine evergreen forest in Colorado USA. We implement the CARDAMOM model-data fusion network to resolve the temperature sensitivity of spring GPP. To capture a GPP temperature limitation – a critical component of integrated sensitivity of GPP to temperature – we introduced a cold temperature scaling function in CARDAMOM to regulate photosynthetic productivity. We found that GPP was gradually inhibited at temperature below 6.0 °C (±2.6 °C) and completely inhibited below −7.1 °C (±1.1 °C). The addition of this scaling factor improved the model’s ability to replicate spring GPP at interannual and decadal time scales (r = 0.88), relative to the nominal CARDAMOM configuration (r = 0.47), and improved spring GPP model predictability outside of the data assimilation training period (r = 0.88) . While cold temperature limitation has an important influence on spring GPP, it does not have a significant impact on integrated growing season GPP, revealing that other environmental controls, such as precipitation, play a more important role in annual productivity. This study highlights growing season onset temperature as a key limiting factor for spring growth in winter-dormant evergreen forests, which is critical in understanding future responses to climate change.