Eric W. Sanderson
Wildlife Conservation Society, 2300 Southern Blvd., Bronx NY 10460
19 January 2014
© Wildlife Conservation Society, 2014
Please submit comments or suggestions to m2409@themannahattaproject.org.
Carbon cycling in nature is complex and much more complicated in urban ecosystems. In Visionmaker NYC, we deploy a integrated carbon model that includes submodels that treat ecosystem carbon (including photosynthesis and respiration), carbon consumption (related to food, food harvests, and waste), and fuel consumption. The fuel consumption submodel includes additional modules for building, transportation, cooking, lighting & appliances, electricity production and consumption, and steam production. The results of each of these estimates are then rolled up into total carbon fluxes through the vision extent as a function of parameters and other metrics associated with ecosystems, lifestyle, and climate scenario selected by the user. Carbon Metrics are all reported on an annual basis.
Ecosystem carbon
Ecosystem carbon is primarily estimated through parameters representing ecosystem-dependent densities, which include plant biomass density, soil organic carbon biomass density, and litterfall biomass density. We calculate the area-weighted average density value across the vision extent and then multiply by the area of the vision extent, resulting in estimates for plant biomass, soil organic matter, and leaves and sticks (i.e. leaf litter and downed wood). A similar approach is taken to the fluxes including net primary productivity to estimate plant growth and litterfall rate density to estimate plant senescence. We do not currently estimate the rate of decomposition of the litterfall, but may do so in a future version of Visionmaker NYC (however, see soil respiration below.)
Animal biomass is estimated separately for human beings, pets, and other wildlife. For people, we add the number of residents, workers and visitors from the population model and then multiply by a lifestyle-dependent average human biomass parameter (reported under carbon > stored > standing biomass > animal biomass > humans in the data summary.) For pets, we similarly multiply the estimated number of cats by an average cat biomass parameter and the number of dogs by an average dog biomass parameter. Other pets are neglected. Wildlife density for all other wild-living species is estimated using an area-weighted wildlife biomass density parameter multiplied by the area of the vision extent similar to the approach taken for plant biomass.
Plant respiration is based on net primary productivity multiplied by a carbon use efficiency assumed to equal 0.5 (c.f. Gifford (2003)). Animal respiration is estimated by summing the animal biomass from people, cats, dogs, and wildlife, and multiplying by a generic "animal respiration rate" parameter. Soil respiration is estimated as described above through an ecosystem-dependent soil respiration density parameter. Plant and animal respiration is reported as photosynthesis and respiration.
Food, harvests and wastes
The reporting of carbon flows is unconventional as it integrates ecosystem carbon stocks and fluxes with carbon flows more commonly associated with human activities typical of towns and cities, notably the consumption of food and the production of solid and liquid waste. Given the current interest in urban agriculture we have also incorporated some metrics of agricultural harvest based on data from New York and New Jersey agricultural practices.
Food consumption is estimated at home based on the number of residents and lifestyle-dependent at-home protein, carbohydrate, fat, and fiber daily consumption rates. Food outside the home is based on the sum of the number of workers plus visitors and corresponding out-of-the home protein, carbohydrate, fat, and fiber daily consumption rates. These daily estimates are multiplied by the number of days per year to estimate annual consumption rates. The amount of food stored ("food in cupboards") is based on the number of days food is stored at home divided by the number of days per year, resulting in estimates for total protein, total carbohydrates, total fat, and total fiber stored within the vision extent.
Food harvest by people are estimated through an area-weighted average of harvest rate densities that depend on ecosystem. Currently only agricultural field / vegetable garden, orchard, and greenhouse / vertical farm ecosystems have nonzero values for this parameter. The actual weight of harvest depends strongly the crop type; in version 1 we pick a representative crop for each ecosystem type, though future versions may provide more detailed estimates. We currently do not estimate harvest wastes. We do estimate harvest by wildlife based on ecosystem-dependent herbivory rate densities, estimated on an area-weighted basis over the vision extent.
The amount of solid wastes are estimated based on a residential solid waste generation rate multiplied by the number of residents plus a use solid waste generation rate density multiplied by the floor area of each use and extrapolated to an annual generation rate. The total waste is broken into a biodegradable (i.e. compostable) solid waste portion based on the lifestyle-dependent organic proportion of solid waste parameter and non-biodegradable solid waste, some of which may not be carboniferous. Compost bins withdraw a fixed proportion of biodegradable solid waste stream, currently fixed at 25%. The amount of solid waste stored (i.e. “waste in baskets”) based on the frequency of waste removal given by the days of waste storage prior to pickup and the days per year. Biodegradable garbage and non-biodegradable garbage are estimated separately.
Fuel combustion
The large magnitude of carbon produced by modern lifestyles is a global concern because of relevance to the Earth’s climate system. Most of that carbon comes from burning fossil fuels. Fossil fuels are consumed in this way because they are relatively energy dense and at one time, were relatively abundant. Other fuels are biomass fuels, like wood and municipal solid waste; combusting these fuels also generates carbon dioxide and methane that enters the atmosphere.
We estimate annual fuel consumption by first estimating energy demand for seven different fuel uses: heating, cooling, cooking, lighting & appliances, transporting people (i.e. personal transportation), transporting stuff (i.e. freight), making electricity, making steam, and using grid electricity. Energy consumption is then divided across fuels using a combination of ecosystem- and lifestyle-dependent parameters (as explained below). Fuel consumption is adjusted for energy losses during conversion of the fuel into the energy source through energy efficiency parameters. Consumption of individual fuels is summed across uses, converted into carbon dioxide and methane emissions using fuel specific emission rates. “Fuels in tanks” refers to the fuel stored with the vision extent and is estimated from a lifestyle- and fuel-dependent days of fuel storage parameter divided by the number of days per year.
Heating and cooling fuel consumption
Buildings use energy to maintain a constant climate indoors even as the climate outdoors changes. For each climate scenario we estimate heating degree days and cooling degree days required over the year. Buildings in the city cluster together, so we estimate the exterior shared wall area of each patch of contiguous buildings by estimating the area of each patch, and then multiplying by the average building height of the “shared wall ecosystems” (i.e. buildings.) The same method allows us to measure the roof area and volume of the shared wall ecosystems within the vision extent.
We consider two heat loss/gain mechanisms when estimating energy demand for climate control: transmission through roofs and walls and infiltration as a result of open doors and windows. For transmission, we estimate an ecosystem-dependent shared wall average U-factor representing the heat gained or lost through walls and an analogously averaged U-factor for heat gained or lost through roofs. The average U-factor is multiplied by the heating degree days and the area of the walls to estimate heat lost through walls; an analogous calculation allows estimate of heat lost through roofs. We estimate heat loss from infiltration through an ecosystem-dependent number of air changes per hour parameter averaged over the shared wall ecosystem types, multiplied by the shared wall volume, the heating degree days, and parameters representing the specific heat capacity of the air and the density of the air, and then extrapolated on an annual basis. Analogous calculations are made for cooling, except using cooling degree days rather than heating degree days.
We estimate the amount of heat generated within buildings by people and their pets and by equipment. Animal heat is estimated from the biomass of people and pets multiplied by an animal heat generation rate. Equipment heat is estimated from a use heat generation rate density multiplied by the floor area of different uses. Heat from these sources is subtracted from the heating requirement and added to the cooling requirement.
The fuels required to meet the climate energy demands are based on lifestyle-dependent parameters describing the proportion of heating provided by different fuels and the proportion of cooling provided by fuels multiplied by the heating and cooling demands, respectively, and divided by fuel-dependent energy efficiencies for heating and cooling and the energy content of each fuel. Estimates are reported in fuels consumed. See additional notes under “Electricity fuel consumption” below to understand how fuels associated with electricity demands are estimated.
Cooking and lighting and appliances fuel consumption
Cooking energy demand is estimated by a cooking energy demand rate density that depends on use, multiplied by the floor area of each use. Lighting & appliances energy demand is also estimated from a lighting and appliances energy demand rate density multiplied by floor area. We estimate the lighting & appliances energy demand of "light industries" (e.g. wind farms, solar energy facilities, tidal energy facilities) as 10% of the energy demand of "heavy industries" (e.g. water treatment plants, solid waste transfer facilities, factories.) Future versions of Visionmaker NYC will treat different kinds of industries with finer distinctions.
The fuels required to meet the cooking and lighting & appliances energy demands are based on lifestyle-dependent parameters describing the proportion of cooking provided by fuels and the proportion of lighting and appliances provided by fuels multiplied by the cooking and lighting & appliance demands, respectively, and divided by fuel-dependent energy efficiency of fuel for cooking and lighting and appliances and the energy content of each fuel. Estimates are reported in fuels consumed. See additional notes under “Electricity fuel consumption” below to understand how fuels associated with electricity demands are estimated.
Transportation fuel consumption
Personal trips and freight trips (i.e. “deliveries and pickups”) are estimated using a series of methodological steps described under the population model.Those models estimate the total distance travelled by personal transport mode and freight mode for trips originating or destined for the vision extent. In the carbon model, we translate miles into fuels.The number of vehicle miles per transportation mode is multiplied by a lifestyle-dependent proportion of personal transport mode miles supplied by fuel parameter divided by the average mileage of that mode with that fuel to estimate fuel consumption. An analogous calculation is made for freight modes and fuels. Estimates are reported in fuels consumed under “transporting people” for personal transportation, and “transporting stuff” for freight transportation. See additional notes under “Electricity fuel consumption” below to understand how fuels associated with electricity demands are estimated.
Electricity fuel consumption
A number of ecosystems model electricity production including photovoltaic panels, solar energy facilities, wind farms, tidal energy facilities, diesel power plants, natural gas power plants, and co-generation plants. We estimate the amount of electricity using an ecosystem-dependent electricity production rate density multiplied by the area of the appropriate ecosystem. Generating electricity for some of these ecosystems consumes fuel. For each energy-producing ecosystem, we estimate fuel consumption by multiplying the energy produced by a proportion of electricity generated by each fuel and dividing by an energy efficiency of the fuel for electricity production and the energy content of fuel.
Electricity production is then compared to electricity consumption as described above. If electricity consumption exceeds production within the vision extent, the deficit is made up with electricity drawn from the power grid. Grid electricity is also generated by fuels. We estimate fuel consumption for grid electricity from a lifestyle-dependent proportion of grid electricity provided by fuel parameter and dividing by an energy efficiency of the fuel for electricity production and the energy content of fuel.
Steam fuel consumption
Only one ecosystem currently generates steam for heating: co-generation plants. Steam fuel consumption is treated analogously as electricity fuel consumption. Water from the amount of steam used for heating within the vision extent is connected to water consumption in the water model.
Validation of the carbon model estimates is on-going. Check back here for updates.